@Preamble{"\input bibnames.sty" #
"\def \TM {${}^{\sc TM}$}"
}
@String{ack-nhfb = "Nelson H. F. Beebe,
University of Utah,
Department of Mathematics, 110 LCB,
155 S 1400 E RM 233,
Salt Lake City, UT 84112-0090, USA,
Tel: +1 801 581 5254,
FAX: +1 801 581 4148,
e-mail: \path|beebe@math.utah.edu|,
\path|beebe@acm.org|,
\path|beebe@computer.org| (Internet),
URL: \path|http://www.math.utah.edu/~beebe/|"}
@String{j-TWEB = "ACM Transactions on the Web (TWEB)"}
@Article{Ashman:2007:I,
author = "Helen Ashman and Arun Iyengar",
title = "Introduction",
journal = j-TWEB,
volume = "1",
number = "1",
pages = "1:1--1:??",
month = may,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1232722.1232723",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:16:53 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Urgaonkar:2007:AMM,
author = "Bhuvan Urgaonkar and Giovanni Pacifici and Prashant
Shenoy and Mike Spreitzer and Asser Tantawi",
title = "Analytic modeling of multitier {Internet}
applications",
journal = j-TWEB,
volume = "1",
number = "1",
pages = "2:1--2:??",
month = may,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1232722.1232724",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:16:53 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Since many Internet applications employ a multitier
architecture, in this article, we focus on the problem
of analytically modeling the behavior of such
applications. We present a model based on a network of
queues where the queues represent different tiers of
the application. Our model is sufficiently general to
capture (i) the behavior of tiers with significantly
different performance characteristics and (ii)
application idiosyncrasies such as session-based
workloads, tier replication, load imbalances across
replicas, and caching at intermediate tiers. We
validate our model using real multitier applications
running on a Linux server cluster. Our experiments
indicate that our model faithfully captures the
performance of these applications for a number of
workloads and configurations. Furthermore, our model
successfully handles a comprehensive range of resource
utilization---from 0 to near saturation for the
CPU---for two separate tiers. For a variety of
scenarios, including those with caching at one of the
application tiers, the average response times predicted
by our model were within the 95\% confidence intervals
of the observed average response times. Our experiments
also demonstrate the utility of the model for dynamic
capacity provisioning, performance prediction,
bottleneck identification, and session policing. In one
scenario, where the request arrival rate increased from
less than 1500 to nearly 4200 requests/minute, a
dynamic provisioning technique employing our model was
able to maintain response time targets by increasing
the capacity of two of the tiers by factors of 2 and
3.5, respectively.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "analytical model; dynamic provisioning; hosting
platform; Internet service; mean-value analysis;
performance prediction; policing; queuing theory;
session; tier",
}
@Article{Jansen:2007:CES,
author = "Bernard J. Jansen",
title = "The comparative effectiveness of sponsored and
nonsponsored links for {Web} e-commerce queries",
journal = j-TWEB,
volume = "1",
number = "1",
pages = "3:1--3:??",
month = may,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1232722.1232725",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:16:53 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The predominant business model for Web search engines
is sponsored search, which generates billions in yearly
revenue. But are sponsored links providing online
consumers with relevant choices for products and
services? We address this and related issues by
investigating the relevance of sponsored and
nonsponsored links for e-commerce queries on the major
search engines. The results show that average relevance
ratings for sponsored and nonsponsored links are
practically the same, although the relevance ratings
for sponsored links are statistically higher. We used
108 ecommerce queries and 8,256 retrieved links for
these queries from three major Web search engines:
Yahoo!, Google, and MSN. In addition to relevance
measures, we qualitatively analyzed the e-commerce
queries, deriving five categorizations of underlying
information needs. Product-specific queries are the
most prevalent (48\%). Title (62\%) and summary (33\%)
are the primary basis for evaluating sponsored links
with URL a distant third (2\%). To gauge the
effectiveness of sponsored search campaigns, we
analyzed the sponsored links from various viewpoints.
It appears that links from organizations with large
sponsored search campaigns are more relevant than the
average sponsored link. We discuss the implications for
Web search engines and sponsored search as a long-term
business model and as a mechanism for finding relevant
information for searchers.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "e-commerce searching; sponsored links; sponsored
results; sponsored search; Web search engines; Web
searching",
}
@Article{Church:2007:MIA,
author = "Karen Church and Barry Smyth and Paul Cotter and Keith
Bradley",
title = "Mobile information access: a study of emerging
search behavior on the mobile {Internet}",
journal = j-TWEB,
volume = "1",
number = "1",
pages = "4:1--4:??",
month = may,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1232722.1232726",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:16:53 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "It is likely that mobile phones will soon come to
rival more traditional devices as the primary platform
for information access. Consequently, it is important
to understand the emerging information access behavior
of mobile Internet (MI) users especially in relation to
their use of mobile handsets for information browsing
and query-based search. In this article, we describe
the results of a recent analysis of the MI habits of
more than 600,000 European MI users, with a particular
emphasis on the emerging interest in mobile search. We
consider a range of factors including whether there are
key differences between browsing and search behavior on
the MI compared to the Web. We highlight how browsing
continues to dominate mobile information access, but go
on to show how search is becoming an increasingly
popular information access alternative especially in
relation to certain types of mobile handsets and
information needs. Moreover, we show that sessions
involving search tend to be longer and more data-rich
than those that do not involve search. We also look at
the type of queries used during mobile search and the
way that these queries tend to be modified during the
course of a mobile search session. Finally we examine
the overlap among mobile search queries and the
different topics mobile users are interested in.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "log analysis; Mobile browsing; mobile Internet; mobile
search",
}
@Article{Leskovec:2007:DVM,
author = "Jure Leskovec and Lada A. Adamic and Bernardo A.
Huberman",
title = "The dynamics of viral marketing",
journal = j-TWEB,
volume = "1",
number = "1",
pages = "5:1--5:??",
month = may,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1232722.1232727",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:16:53 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We present an analysis of a person-to-person
recommendation network, consisting of 4 million people
who made 16 million recommendations on half a million
products. We observe the propagation of recommendations
and the cascade sizes, which we explain by a simple
stochastic model. We analyze how user behavior varies
within user communities defined by a recommendation
network. Product purchases follow a `long tail' where a
significant share of purchases belongs to rarely sold
items. We establish how the recommendation network
grows over time and how effective it is from the
viewpoint of the sender and receiver of the
recommendations. While on average recommendations are
not very effective at inducing purchases and do not
spread very far, we present a model that successfully
identifies communities, product, and pricing categories
for which viral marketing seems to be very effective.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "e-commerce; long tail; network analysis; recommender
systems; Viral marketing; word-of-mouth",
}
@Article{Yu:2007:EAW,
author = "Tao Yu and Yue Zhang and Kwei-Jay Lin",
title = "Efficient algorithms for {Web} services selection with
end-to-end {QoS} constraints",
journal = j-TWEB,
volume = "1",
number = "1",
pages = "6:1--6:??",
month = may,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1232722.1232728",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:16:53 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Service-Oriented Architecture (SOA) provides a
flexible framework for service composition. Using
standard-based protocols (such as SOAP and WSDL),
composite services can be constructed by integrating
atomic services developed independently. Algorithms are
needed to select service components with various QoS
levels according to some application-dependent
performance requirements. We design a broker-based
architecture to facilitate the selection of QoS-based
services. The objective of service selection is to
maximize an application-specific utility function under
the end-to-end QoS constraints. The problem is modeled
in two ways: the combinatorial model and the graph
model. The combinatorial model defines the problem as a
multidimension multichoice 0-1 knapsack problem (MMKP).
The graph model defines the problem as a
multiconstraint optimal path (MCOP) problem. Efficient
heuristic algorithms for service processes of different
composition structures are presented in this article
and their performances are studied by simulations. We
also compare the pros and cons between the two
models.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "End-to-end QoS; service composition; service oriented
architecture (SOA); service selection; Web services",
}
@Article{Dubinko:2007:VTT,
author = "Micah Dubinko and Ravi Kumar and Joseph Magnani and
Jasmine Novak and Prabhakar Raghavan and Andrew
Tomkins",
title = "Visualizing tags over time",
journal = j-TWEB,
volume = "1",
number = "2",
pages = "7:1--7:??",
month = aug,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1255438.1255439",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We consider the problem of visualizing the evolution
of tags within the Flickr (flickr.com) online image
sharing community. Any user of the Flickr service may
append a tag to any photo in the system. Over the past
year, users have on average added over a million tags
each week. Understanding the evolution of these tags
over time is therefore a challenging task. We present a
new approach based on a characterization of the most
interesting tags associated with a sliding interval of
time. An animation provided via Flash in a Web browser
allows the user to observe and interact with the
interesting tags as they evolve over time.\par
New algorithms and data structures are required to
support the efficient generation of this visualization.
We combine a novel solution to an interval covering
problem with extensions to previous work on score
aggregation in order to create an efficient backend
system capable of producing visualizations at arbitrary
scales on this large dataset in real time.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Flickr; interval covering; tags; temporal evolution;
visualization",
}
@Article{Mohan:2007:SPC,
author = "Bharath Kumar Mohan and Benjamin J. Keller and Naren
Ramakrishnan",
title = "Scouts, promoters, and connectors: {The} roles of
ratings in nearest-neighbor collaborative filtering",
journal = j-TWEB,
volume = "1",
number = "2",
pages = "8:1--8:??",
month = aug,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1255438.1255440",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Recommender systems aggregate individual user ratings
into predictions of products or services that might
interest visitors. The quality of this aggregation
process crucially affects the user experience and hence
the effectiveness of recommenders in e-commerce. We
present a characterization of nearest-neighbor
collaborative filtering that allows us to disaggregate
global recommender performance measures into
contributions made by each individual rating. In
particular, we formulate three roles--- {\em scouts},
{\em promoters}, and {\em connectors\/} ---that capture
how users receive recommendations, how items get
recommended, and how ratings of these two types are
themselves connected, respectively. These roles find
direct uses in improving recommendations for users, in
better targeting of items and, most importantly, in
helping monitor the health of the system as a whole.
For instance, they can be used to track the evolution
of neighborhoods, to identify rating subspaces that do
not contribute (or contribute negatively) to system
performance, to enumerate users who are in danger of
leaving, and to assess the susceptibility of the system
to attacks such as shilling. We argue that the three
rating roles presented here provide broad primitives to
manage a recommender system and its community.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "collaborative filtering; connectors; neighborhoods;
promoters; Recommender systems; scouts; user-based and
item-based algorithms",
}
@Article{Rogers:2007:EPB,
author = "Alex Rogers and Esther David and Nicholas R. Jennings
and Jeremy Schiff",
title = "The effects of proxy bidding and minimum bid
increments within {eBay} auctions",
journal = j-TWEB,
volume = "1",
number = "2",
pages = "9:1--9:??",
month = aug,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1255438.1255441",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We present a mathematical model of the eBay auction
protocol and perform a detailed analysis of the effects
that the eBay proxy bidding system and the minimum bid
increment have on the auction properties. We first
consider the revenue of the auction, and we show
analytically that when two bidders with independent
private valuations use the eBay proxy bidding system
there exists an optimal value for the minimum bid
increment at which the auctioneer's revenue is
maximized. We then consider the sequential way in which
bids are placed within the auction, and we show
analytically that independent of assumptions regarding
the bidders' valuation distribution or bidding strategy
the number of visible bids placed is related to the
logarithm of the number of potential bidders. Thus, in
many cases, it is only a minority of the potential
bidders that are able to submit bids and are visible in
the auction bid history (despite the fact that the
other hidden bidders are still effectively competing
for the item). Furthermore, we show through simulation
that the minimum bid increment also introduces an
inefficiency to the auction, whereby a bidder who
enters the auction late may find that its valuation is
insufficient to allow them to advance the current bid
by the minimum bid increment despite them actually
having the highest valuation for the item. Finally, we
use these results to consider appropriate strategies
for bidders within real world eBay auctions. We show
that while last-minute bidding (sniping) is an
effective strategy against bidders engaging in
incremental bidding (and against those with common
values), in general, delaying bidding is
disadvantageous even if delayed bids are sure to be
received before the auction closes. Thus, when several
bidders submit last-minute bids, we show that rather
than seeking to bid as late as possible, a bidder
should try to be the first sniper to bid (i.e., it
should ``snipe before the snipers'').",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "bid increment; electronic commerce; Online auctions;
proxy bidding; sniping",
}
@Article{Serrano:2007:DSW,
author = "M. {\'A}ngeles Serrano and Ana Maguitman and
Mari{\'a}n Bogu{\~n}{\'a} and Santo Fortunato and
Alessandro Vespignani",
title = "Decoding the structure of the {WWW}: a comparative
analysis of {Web} crawls",
journal = j-TWEB,
volume = "1",
number = "2",
pages = "10:1--10:??",
month = aug,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1255438.1255442",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The understanding of the immense and intricate
topological structure of the World Wide Web (WWW) is a
major scientific and technological challenge. This has
been recently tackled by characterizing the properties
of its representative graphs, in which vertices and
directed edges are identified with Web pages and
hyperlinks, respectively. Data gathered in large-scale
crawls have been analyzed by several groups resulting
in a general picture of the WWW that encompasses many
of the complex properties typical of rapidly evolving
networks. In this article, we report a detailed
statistical analysis of the topological properties of
four different WWW graphs obtained with different
crawlers. We find that, despite the very large size of
the samples, the statistical measures characterizing
these graphs differ quantitatively, and in some cases
qualitatively, depending on the domain analyzed and the
crawl used for gathering the data. This spurs the issue
of the presence of sampling biases and structural
differences of Web crawls that might induce properties
not representative of the actual global underlying
graph. In short, the stability of the widely accepted
statistical description of the Web is called into
question. In order to provide a more accurate
characterization of the Web graph, we study statistical
measures beyond the degree distribution, such as
degree-degree correlation functions or the statistics
of reciprocal connections. The latter appears to
enclose the relevant correlations of the WWW graph and
carry most of the topological information of the Web.
The analysis of this quantity is also of major interest
in relation to the navigability and searchability of
the Web.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "crawler biases; statistical analysis; Web graph
structure; Web measurement",
}
@Article{Reis:2007:BVD,
author = "Charles Reis and John Dunagan and Helen J. Wang and
Opher Dubrovsky and Saher Esmeir",
title = "{BrowserShield}: {Vulnerability}-driven filtering of
dynamic {HTML}",
journal = j-TWEB,
volume = "1",
number = "3",
pages = "11:1--11:??",
month = sep,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1281480.1281481",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:14 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Vulnerability-driven filtering of network data can
offer a fast and easy-to-deploy alternative or
intermediary to software patching, as exemplified in
Shield [Wang et al. 2004]. In this article, we take
Shield's vision to a new domain, inspecting and
cleansing not just static content, but also dynamic
content. The dynamic content we target is the dynamic
HTML in Web pages, which have become a popular vector
for attacks. The key challenge in filtering dynamic
HTML is that it is undecidable to statically determine
whether an embedded script will exploit the browser at
runtime. We avoid this undecidability problem by
rewriting web pages and any embedded scripts into safe
equivalents, inserting checks so that the filtering is
done at runtime. The rewritten pages contain logic for
recursively applying runtime checks to dynamically
generated or modified web content, based on known
vulnerabilities. We have built and evaluated {\em
BrowserShield}, a general framework that performs this
dynamic instrumentation of embedded scripts, and that
admits policies for customized runtime actions like
vulnerability-driven filtering. We also explore other
applications on top of BrowserShield.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "code rewriting; JavaScript; vulnerability; Web
browser",
}
@Article{Sun:2007:MDW,
author = "Zan Sun and Jalal Mahmud and I. V. Ramakrishnan and
Saikat Mukherjee",
title = "Model-directed {Web} transactions under constrained
modalities",
journal = j-TWEB,
volume = "1",
number = "3",
pages = "12:1--12:??",
month = sep,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1281480.1281482",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:14 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Online transactions (e.g., buying a book on the Web)
typically involve a number of steps spanning several
pages. Conducting such transactions under constrained
interaction modalities as exemplified by small screen
handhelds or interactive speech interfaces --- the
primary mode of communication for visually impaired
individuals --- is a strenuous, fatigue-inducing
activity. But usually one needs to browse only a small
fragment of a Web page to perform a transactional step
such as a form fillout, selecting an item from a search
results list, and so on. We exploit this observation to
develop an automata-based process model that delivers
only the ``relevant'' page fragments at each
transactional step, thereby reducing information
overload on such narrow interaction bandwidths. We
realize this model by coupling techniques from content
analysis of Web documents, automata learning and
statistical classification. The process model and
associated techniques have been incorporated into
Guide-O, a prototype system that facilitates online
transactions using speech/keyboard interface
(Guide-O-Speech), or with limited-display size
handhelds (Guide-O-Mobile). Performance of Guide-O and
its user experience are reported.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "assistive device; content adaption; Web transaction",
}
@Article{Sharman:2007:CAD,
author = "Raj Sharman and Shiva Shankar Ramanna and Ram Ramesh
and Ram Gopal",
title = "Cache architecture for on-demand streaming on the
{Web}",
journal = j-TWEB,
volume = "1",
number = "3",
pages = "13:1--13:??",
month = sep,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1281480.1281483",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:14 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "On-demand streaming from a remote server through
best-effort Internet poses several challenges because
of network losses and variable delays. The primary
technique used to improve the quality of distributed
content service is replication. In the context of the
Internet, Web caching is the traditional mechanism that
is used. In this article we develop a new staged
delivery model for a distributed architecture in which
video is streamed from remote servers to edge caches
where the video is buffered and then streamed to the
client through a last-mile connection. The model uses a
novel revolving indexed cache buffer management
mechanism at the edge cache and employs selective
retransmissions of lost packets between the remote and
edge cache for a best-effort recovery of the losses.
The new Web cache buffer management scheme includes a
dynamic adjustment of cache buffer parameters based on
network conditions. In addition, performance of buffer
management and retransmission policies at the edge
cache is modeled and assessed using a probabilistic
analysis of the streaming process as well as system
simulations. The influence of different endogenous
control parameters on the quality of stream received by
the client is studied. Calibration curves on the QoS
metrics for different network conditions have been
obtained using simulations. Edge cache management can
be done using these calibration curves. ISPs can make
use of calibration curves to set the values of the
endogenous control parameters for specific QoS in
real-time streaming operations based on network
conditions. A methodology to benchmark transmission
characteristics using real-time traffic data is
developed to enable effective decision making on edge
cache buffer allocation and management strategies.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "buffering; edge cache; on-demand streaming; quality of
service; selective retransmissions; Web caching",
}
@Article{Zdun:2007:MPD,
author = "Uwe Zdun and Carsten Hentrich and Schahram Dustdar",
title = "Modeling process-driven and service-oriented
architectures using patterns and pattern primitives",
journal = j-TWEB,
volume = "1",
number = "3",
pages = "14:1--14:??",
month = sep,
year = "2007",
CODEN = "????",
DOI = "https://doi.org/10.1145/1281480.1281484",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:14 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Service-oriented architectures are increasingly used
in the context of business processes. However, the
proven practices for process-oriented integration of
services are not well documented yet. In addition,
modeling approaches for the integration of processes
and services are neither mature nor do they exactly
reflect the proven practices. In this article, we
propose a pattern language for process-oriented
integration of services to describe the proven
practices. Our main contribution is a modeling concept
based on pattern primitives for these patterns. A
pattern primitive is a fundamental, precisely specified
modeling element that represents a pattern. We present
a catalog of pattern primitives that are precisely
modeled using OCL constraints and map these primitives
to the patterns in the pattern language of
process-oriented integration of services. We also
present a model validation tool that we have developed
to support modeling the process-oriented integration of
services, and an industrial case study in which we have
applied our results.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "middleware; Service-oriented architecture; software
patterns",
}
@Article{Najork:2008:ISS,
author = "Marc Najork and Brian D. Davison",
title = "Introduction to special section on adversarial issues
in {Web} search",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "1:1--1:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326562",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Becchetti:2008:LAW,
author = "Luca Becchetti and Carlos Castillo and Debora Donato
and Ricardo Baeza-Yates and Stefano Leonardi",
title = "Link analysis for {Web} spam detection",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "2:1--2:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326563",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We propose link-based techniques for automatic
detection of Web spam, a term referring to pages which
use deceptive techniques to obtain undeservedly high
scores in search engines. The use of Web spam is
widespread and difficult to solve, mostly due to the
large size of the Web which means that, in practice,
many algorithms are infeasible.\par
We perform a statistical analysis of a large collection
of Web pages. In particular, we compute statistics of
the links in the vicinity of every Web page applying
rank propagation and probabilistic counting over the
entire Web graph in a scalable way. These statistical
features are used to build Web spam classifiers which
only consider the link structure of the Web, regardless
of page contents. We then present a study of the
performance of each of the classifiers alone, as well
as their combined performance, by testing them over a
large collection of Web link spam. After tenfold
cross-validation, our best classifiers have a
performance comparable to that of state-of-the-art spam
classifiers that use content attributes, but are
orthogonal to content-based methods.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "adversarial information retrieval; Link analysis",
}
@Article{Urvoy:2008:TWS,
author = "Tanguy Urvoy and Emmanuel Chauveau and Pascal Filoche
and Thomas Lavergne",
title = "Tracking {Web} spam with {HTML} style similarities",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "3:1--3:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326564",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Automatically generated content is ubiquitous in the
web: dynamic sites built using the three-tier paradigm
are good examples (e.g., commercial sites, blogs and
other sites edited using web authoring software), as
well as less legitimate spamdexing attempts (e.g., link
farms, faked directories).\par
Those pages built using the same generating method
(template or script) share a common ``look and feel''
that is not easily detected by common text
classification methods, but is more related to
stylometry.\par
In this work we study and compare several HTML style
similarity measures based on both textual and
extra-textual features in HTML source code. We also
propose a flexible algorithm to cluster a large
collection of documents according to these measures.
Since the proposed algorithm is based on locality
sensitive hashing (LSH), we first review this
technique.\par
We then describe how to use the HTML style similarity
clusters to pinpoint dubious pages and enhance the
quality of spam classifiers. We present an evaluation
of our algorithm on the WEBSPAM-UK2006 dataset.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Clustering; document similarity; search engine spam;
stylometry; templates identification",
}
@Article{Lin:2008:DST,
author = "Yu-Ru Lin and Hari Sundaram and Yun Chi and Junichi
Tatemura and Belle L. Tseng",
title = "Detecting splogs via temporal dynamics using
self-similarity analysis",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "4:1--4:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326565",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This article addresses the problem of spam blog
(splog) detection using temporal and structural
regularity of content, post time and links. Splogs are
undesirable blogs meant to attract search engine
traffic, used solely for promoting affiliate sites.
Blogs represent popular online media, and splogs not
only degrade the quality of search engine results, but
also waste network resources. The splog detection
problem is made difficult due to the lack of stable
content descriptors.\par
We have developed a new technique for detecting splogs,
based on the observation that a blog is a dynamic,
growing sequence of entries (or posts) rather than a
collection of individual pages. In our approach, splogs
are recognized by their temporal characteristics and
content. There are three key ideas in our splog
detection framework. (a) We represent the blog temporal
dynamics using self-similarity matrices defined on the
histogram intersection similarity measure of the time,
content, and link attributes of posts, to investigate
the temporal changes of the post sequence. (b) We study
the blog temporal characteristics using a visual
representation derived from the self-similarity
measures. The visual signature reveals correlation
between attributes and posts, depending on the type of
blogs (normal blogs and splogs). (c) We propose two
types of novel temporal features to capture the splog
temporal characteristics. In our splog detector, these
novel features are combined with content based
features. We extract a content based feature vector
from blog home pages as well as from different parts of
the blog. The dimensionality of the feature vector is
reduced by Fisher linear discriminant analysis. We have
tested an SVM-based splog detector using proposed
features on real world datasets, with appreciable
results (90\% accuracy).",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Blogs; regularity; self-similarity; spam; splog
detection; temporal dynamics; topology",
}
@Article{Weinreich:2008:QAE,
author = "Harald Weinreich and Hartmut Obendorf and Eelco Herder
and Matthias Mayer",
title = "Not quite the average: an empirical study of {Web}
use",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "5:1--5:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326566",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In the past decade, the World Wide Web has been
subject to dramatic changes. Web sites have evolved
from static information resources to dynamic and
interactive applications that are used for a broad
scope of activities on a daily basis. To examine the
consequences of these changes on user behavior, we
conducted a long-term client-side Web usage study with
twenty-five participants. This report presents results
of this study and compares the user behavior with
previous long-term browser usage studies, which range
in age from seven to thirteen years. Based on the
empirical data and the interview results, various
implications for the interface design of browsers and
Web sites are discussed.\par
A major finding is the decreasing prominence of
backtracking in Web navigation. This can largely be
attributed to the increasing importance of dynamic,
service-oriented Web sites. Users do not navigate on
these sites searching for information, but rather
interact with an online application to complete certain
tasks. Furthermore, the usage of multiple windows and
tabs has partly replaced back button usage, posing new
challenges for user orientation and backtracking. We
found that Web browsing is a rapid activity even for
pages with substantial content, which calls for page
designs that allow for cursory reading. Click maps
provide additional information on how users interact
with the Web on page level. Finally, substantial
differences were observed between users, and
characteristic usage patterns for different types of
Web sites emphasize the need for more adaptive and
customizable Web browsers.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "browser interfaces; hypertext; Navigation; usability;
user study; Web; web browsing; web design; WWW",
}
@Article{Yu:2008:FWS,
author = "Qi Yu and Athman Bouguettaya",
title = "Framework for {Web} service query algebra and
optimization",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "6:1--6:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326567",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We present a query algebra that supports optimized
access of Web services through service-oriented
queries. The service query algebra is defined based on
a formal service model that provides a high-level
abstraction of Web services across an application
domain. The algebra defines a set of algebraic
operators. Algebraic service queries can be formulated
using these operators. This allows users to query their
desired services based on both functionality and
quality. We provide the implementation of each
algebraic operator. This enables the generation of
Service Execution Plans (SEPs) that can be used by
users to directly access services. We present an
optimization algorithm by extending the Dynamic
Programming (DP) approach to efficiently select the
SEPs with the best user-desired quality. The
experimental study validates the proposed algorithm by
demonstrating significant performance improvement
compared with the traditional DP approach.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "query optimization; service oriented computing;
service query; Web service",
}
@Article{Aleman-Meza:2008:SSA,
author = "Boanerges Aleman-Meza and Meenakshi Nagarajan and Li
Ding and Amit Sheth and I. Budak Arpinar and Anupam
Joshi and Tim Finin",
title = "Scalable semantic analytics on social networks for
addressing the problem of conflict of interest
detection",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "7:1--7:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326568",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In this article, we demonstrate the applicability of
semantic techniques for detection of Conflict of
Interest (COI). We explain the common challenges
involved in building scalable Semantic Web
applications, in particular those addressing
connecting-the-dots problems. We describe in detail the
challenges involved in two important aspects on
building Semantic Web applications, namely, data
acquisition and entity disambiguation (or reference
reconciliation). We extend upon our previous work where
we integrated the collaborative network of a subset of
DBLP researchers with persons in a Friend-of-a-Friend
social network (FOAF). Our method finds the connections
between people, measures collaboration strength, and
includes heuristics that use friendship/affiliation
information to provide an estimate of potential COI in
a peer-review scenario. Evaluations are presented by
measuring what could have been the COI between accepted
papers in various conference tracks and their
respective program committee members. The experimental
results demonstrate that scalability can be achieved by
using a dataset of over 3 million entities (all
bibliographic data from DBLP and a large collection of
FOAF documents).",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "conflict of interest; data fusion; DBLP; entity
disambiguation; ontologies; peer review process; RDF;
semantic analytics; semantic associations; Semantic
Web; social networks; swetoDblp",
}
@Article{Gmach:2008:AQS,
author = "Daniel Gmach and Stefan Krompass and Andreas Scholz
and Martin Wimmer and Alfons Kemper",
title = "Adaptive quality of service management for enterprise
services",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "8:1--8:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326569",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In the past, enterprise resource planning systems were
designed as monolithic software systems running on
centralized mainframes. Today, these systems are
(re-)designed as a repository of enterprise services
that are distributed throughout the available computing
infrastructure. These service oriented architectures
(SOAs) require advanced automatic and adaptive
management concepts in order to achieve a high quality
of service level in terms of, for example,
availability, responsiveness, and throughput. The
adaptive management has to allocate service instances
to computing resources, adapt the resource allocation
to unforeseen load fluctuations, and intelligently
schedule individual requests to guarantee negotiated
service level agreements (SLAs). Our AutoGlobe platform
provides such a comprehensive adaptive service
management comprising\par
--- static service-to-server allocation based on
automatically detected service utilization
patterns,\par
--- adaptive service management based on a fuzzy
controller that remedies exceptional situations by
automatically initiating, for example, service
migration, service replication (scale-out), and\par
--- adaptive scheduling of individual service requests
that prioritizes requests depending on the current
degree of service level conformance.\par
All three complementary control components are
described in detail, and their effectiveness is
analyzed by means of realistic business application
scenarios.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "fuzzy controller; Quality of service; workload
characterization",
}
@Article{Yang:2008:DGN,
author = "Bo Yang and Jiming Liu",
title = "Discovering global network communities based on local
centralities",
journal = j-TWEB,
volume = "2",
number = "1",
pages = "9:1--9:??",
month = feb,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1326561.1326570",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:25 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "One of the central problems in studying and
understanding complex networks, such as online social
networks or World Wide Web, is to discover hidden,
either physically (e.g., interactions or hyperlinks) or
logically (e.g., profiles or semantics) well-defined
topological structures. From a practical point of view,
a good example of such structures would be so-called
network communities. Earlier studies have introduced
various formulations as well as methods for the problem
of identifying or extracting communities. While each of
them has pros and cons as far as the effectiveness and
efficiency are concerned, almost none of them has
explicitly dealt with the potential relationship
between the global topological property of a network
and the local property of individual nodes. In order to
study this problem, this paper presents a new
algorithm, called ICS, which aims to discover natural
network communities by inferring from the local
information of nodes inherently hidden in networks
based on a new centrality, that is, clustering
centrality, which is a generalization of eigenvector
centrality. As compared with existing methods, our
method runs efficiently with a good clustering
performance. Additionally, it is insensitive to its
built-in parameters and prior knowledge.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "centrality; community mining; Complex network; graph
theory; World Wide Web",
}
@Article{Dustdar:2008:ISI,
author = "Schahram Dustdar and Bernd J. Kr{\"a}mer",
title = "Introduction to special issue on service oriented
computing {(SOC)}",
journal = j-TWEB,
volume = "2",
number = "2",
pages = "10:1--10:??",
month = apr,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1346337.1346338",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:47 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Belhajjame:2008:AAW,
author = "Khalid Belhajjame and Suzanne M. Embury and Norman W.
Paton and Robert Stevens and Carole A. Goble",
title = "Automatic annotation of {Web} services based on
workflow definitions",
journal = j-TWEB,
volume = "2",
number = "2",
pages = "11:1--11:??",
month = apr,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1346237.1346239",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:47 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Semantic annotations of web services can support the
effective and efficient discovery of services, and
guide their composition into workflows. At present,
however, the practical utility of such annotations is
limited by the small number of service annotations
available for general use. Manual annotation of
services is a time consuming and thus expensive task,
so some means are required by which services can be
automatically (or semi-automatically) annotated. In
this paper, we show how information can be inferred
about the semantics of operation parameters based on
their connections to other (annotated) operation
parameters within tried-and-tested workflows. Because
the data links in the workflows do not necessarily
contain every possible connection of compatible
parameters, we can infer only constraints on the
semantics of parameters. We show that despite their
imprecise nature these so-called {\em loose
annotations\/} are still of value in supporting the
manual annotation task, inspecting workflows and
discovering services. We also show that derived
annotations for already annotated parameters are
useful. By comparing existing and newly derived
annotations of operation parameters, we can support the
detection of errors in existing annotations, the
ontology used for annotation and in workflows. The
derivation mechanism has been implemented, and its
practical applicability for inferring new annotations
has been established through an experimental
evaluation. The usefulness of the derived annotations
is also demonstrated.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "automatic annotation; ontologies; semantic
annotations; Semantic web services; workflows",
}
@Article{Elgedawy:2008:CAH,
author = "Islam Elgedawy and Zahir Tari and James A. Thom",
title = "Correctness-aware high-level functional matching
approaches for semantic {Web} services",
journal = j-TWEB,
volume = "2",
number = "2",
pages = "12:1--12:??",
month = apr,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1346237.1346240",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:47 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Service matching approaches trade precision for
recall, creating the need for users to choose the
correct services, which obviously is a major obstacle
for automating the service discovery and aggregation
processes. Our approach to overcome this problem, is to
eliminate the appearance of false positives by
returning only the correct services. As different users
have different semantics for what is correct, we argue
that the correctness of the matching results must be
determined according to the achievement of users'
goals: that only services achieving users' goals are
considered correct. To determine such correctness, we
argue that the matching process should be based
primarily on the high-level functional specifications
(namely goals, achievement contexts, and external
behaviors). In this article, we propose models, data
structures, algorithms, and theorems required to
correctly match such specifications. We propose a model
called $ G^+ $, to capture such specifications, for
both services and users, in a machine-understandable
format. We propose a data structure, called a Concepts
Substitutability Graph (CSG), to capture the
substitution semantics of application domain concepts
in a context-based manner, in order to determine the
semantic-preserving mapping transformations required to
match different {\em G\/}$^+$ models. We also propose a
behavior matching approach that is able to match states
in an m-to-n manner, such that behavior models with
different numbers of state transitions can be matched.
Finally, we show how services are matched and
aggregated according to their $ G^+ $ models. Results
of supporting experiments demonstrate the advantages of
the proposed service matching approaches.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "High-level functional matching; semantic Web services;
service aggregation",
}
@Article{Ryu:2008:SDE,
author = "Seung Hwan Ryu and Fabio Casati and Halvard Skogsrud
and Boualem Benatallah and R{\'e}gis Saint-Paul",
title = "Supporting the dynamic evolution of {Web} service
protocols in service-oriented architectures",
journal = j-TWEB,
volume = "2",
number = "2",
pages = "13:1--13:??",
month = apr,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1346237.1346241",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:47 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In service-oriented architectures, everything is a
service and everyone is a service provider. Web
services (or simply services) are loosely coupled
software components that are published, discovered, and
invoked across the Web. As the use of Web service
grows, in order to correctly interact with them, it is
important to understand the business protocols that
provide clients with the information on how to interact
with services. In dynamic Web service environments,
service providers need to constantly adapt their
business protocols for reflecting the restrictions and
requirements proposed by new applications, new business
strategies, and new laws, or for fixing problems found
in the protocol definition. However, the effective
management of such a protocol evolution raises critical
problems: one of the most critical issues is how to
handle instances running under the old protocol when it
has been changed. Simple solutions, such as aborting
them or allowing them to continue to run according to
the old protocol, can be considered, but they are
inapplicable for many reasons (for example, the loss of
work already done and the critical nature of work). In
this article, we present a framework that supports
service managers in managing the business protocol
evolution by providing several features, such as a
variety of protocol change impact analyses
automatically determining which ongoing instances can
be migrated to the new version of protocol, and data
mining techniques inferring interaction patterns used
for classifying ongoing instances migrateable to the
new protocol. To support the protocol evolution
process, we have also developed database-backed GUI
tools on top of our existing system. The proposed
approach and tools can help service managers in
managing the evolution of ongoing instances when the
business protocols of services with which they are
interacting have changed.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Business protocols; change impact analysis; decision
trees; dynamic evolution; ongoing instances; Web
services",
}
@Article{Schafer:2008:EFA,
author = "Michael Sch{\"a}fer and Peter Dolog and Wolfgang
Nejdl",
title = "An environment for flexible advanced compensations of
{Web} service transactions",
journal = j-TWEB,
volume = "2",
number = "2",
pages = "14:1--14:??",
month = apr,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1346237.1346242",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:47 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Business to business integration has recently been
performed by employing Web service environments.
Moreover, such environments are being provided by major
players on the technology markets. Those environments
are based on open specifications for transaction
coordination. When a failure in such an environment
occurs, a compensation can be initiated to recover from
the failure. However, current environments have only
limited capabilities for compensations, and are usually
based on backward recovery. In this article, we
introduce an environment to deal with advanced
compensations based on forward recovery principles. We
extend the existing Web service transaction
coordination architecture and infrastructure in order
to support flexible compensation operations. We use a
contract-based approach, which allows the specification
of permitted compensations at runtime. We introduce
{\em abstract service\/} and {\em adapter\/}
components, which allow us to separate the compensation
logic from the coordination logic. In this way, we can
easily plug in or plug out different compensation
strategies based on a specification language defined on
top of basic compensation activities and complex
compensation types. Experiments with our approach and
environment show that such an approach to compensation
is feasible and beneficial. Additionally, we introduce
a cost-benefit model to evaluate the proposed
environment based on net value analysis. The evaluation
shows in which circumstances the environment is
economical.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "compensations; forward-recovery; transactions; Web
services",
}
@Article{Srivatsa:2008:MAL,
author = "Mudhakar Srivatsa and Arun Iyengar and Jian Yin and
Ling Liu",
title = "Mitigating application-level denial of service attacks
on {Web} servers: a client-transparent approach",
journal = j-TWEB,
volume = "2",
number = "3",
pages = "15:1--15:??",
month = jul,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1377488.1377489",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:58 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Recently, we have seen increasing numbers of denial of
service (DoS) attacks against online services and Web
applications either for extortion reasons or for
impairing and even disabling the competition. These DoS
attacks have increasingly targeted the application
level. Application-level DoS attacks emulate the same
request syntax and network-level traffic
characteristics as those of legitimate clients, thereby
making the attacks much harder to detect and counter.
Moreover, such attacks often target bottleneck
resources such as disk bandwidth, database bandwidth,
and CPU resources. In this article, we propose handling
DoS attacks by using a twofold mechanism. First, we
perform admission control to limit the number of
concurrent clients served by the online service.
Admission control is based on port hiding that renders
the online service invisible to unauthorized clients by
hiding the port number on which the service accepts
incoming requests. Second, we perform congestion
control on admitted clients to allocate more resources
to good clients. Congestion control is achieved by
adaptively setting a client's priority level in
response to the client's requests in a way that can
incorporate application-level semantics. We present a
detailed evaluation of the proposed solution using two
sample applications: Apache HTTPD and the TPCW
benchmark (running on Apache Tomcat and IBM DB2). Our
experiments show that the proposed solution incurs low
performance overhead and is resilient to DoS attacks.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "client transparency; DoS Attacks; game theory; Web
servers",
}
@Article{White:2008:LPD,
author = "Ryen W. White and Mikhail Bilenko and Silviu
Cucerzan",
title = "Leveraging popular destinations to enhance {Web}
search interaction",
journal = j-TWEB,
volume = "2",
number = "3",
pages = "16:1--16:??",
month = jul,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1377488.1377490",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:58 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This article presents a novel Web search interaction
feature that for a given query provides links to Web
sites frequently visited by other users with similar
information needs. These popular destinations
complement traditional search results, allowing direct
navigation to authoritative resources for the query
topic. Destinations are identified using the history of
the search and browsing behavior of many users over an
extended time period, and their collective behavior
provides a basis for computing source authority. They
are drawn from the end of users' postquery browse
trails where users may cease searching once they find
relevant information. We describe a user study that
compared the suggestion of destinations with the
previously proposed suggestion of related queries as
well as with traditional, unaided Web search. Results
show that search enhanced by query suggestions
outperforms other systems in terms of subject
perceptions and search effectiveness for fact-finding
search tasks. However, search enhanced by destination
suggestions performs best for exploratory tasks with
its best performance obtained from mining past user
behavior at query-level granularity. We discuss the
implications of these and other findings from our study
for the design of search systems that utilize user
behavior, in particular, user browse trails and popular
destinations.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "enhanced Web search; search destinations; User
studies",
}
@Article{Andreolini:2008:MFS,
author = "Mauro Andreolini and Sara Casolari and Michele
Colajanni",
title = "Models and framework for supporting runtime decisions
in {Web-based} systems",
journal = j-TWEB,
volume = "2",
number = "3",
pages = "17:1--17:??",
month = jul,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1377488.1377491",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:17:58 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Efficient management of distributed Web-based systems
requires several mechanisms that decide on request
dispatching, load balance, admission control, request
redirection. The algorithms behind these mechanisms
typically make fast decisions on the basis of the load
conditions of the system resources. The architecture
complexity and workloads characterizing most Web-based
services make it extremely difficult to deduce a
representative view of a resource load from collected
measures that show extreme variability even at
different time scales. Hence, any decision based on
instantaneous or average views of the system load may
lead to useless or even wrong actions. As an
alternative, we propose a two-phase strategy that first
aims to obtain a representative view of the load trend
from measured system values and then applies this
representation to support runtime decision systems. We
consider two classical problems behind decisions: how
to detect significant and nontransient load changes of
a system resource and how to predict its future load
behavior. The two-phase strategy is based on stochastic
functions that are characterized by a computational
complexity that is compatible with runtime decisions.
We describe, test, and tune the two-phase strategy by
considering as a first example a multitier Web-based
system that is subject to different classes of
realistic and synthetic workloads. Also, we integrate
the proposed strategy into a framework that we validate
by applying it to support runtime decisions in a
cluster Web system and in a locally distributed Network
Intrusion Detection System.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "distributed systems; load change detection; load
prediction; load representation; World Wide Web",
}
@Article{Amitay:2008:ISI,
author = "Einat Amitay and Andrei Broder",
title = "Introduction to special issue on query log analysis:
{Technology} and ethics",
journal = j-TWEB,
volume = "2",
number = "4",
pages = "18:1--18:??",
month = oct,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1409220.1409221",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cooper:2008:SQL,
author = "Alissa Cooper",
title = "A survey of query log privacy-enhancing techniques
from a policy perspective",
journal = j-TWEB,
volume = "2",
number = "4",
pages = "19:1--19:??",
month = oct,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1409220.1409222",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "As popular search engines face the sometimes
conflicting interests of protecting privacy while
retaining query logs for a variety of uses, numerous
technical measures have been suggested to both enhance
privacy and preserve at least a portion of the utility
of query logs. This article seeks to assess seven of
these techniques against three sets of criteria: (1)
how well the technique protects privacy, (2) how well
the technique preserves the utility of the query logs,
and (3) how well the technique might be implemented as
a user control. A user control is defined as a
mechanism that allows individual Internet users to
choose to have the technique applied to their own query
logs.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "log; policy; Privacy; query; search",
}
@Article{Baeza-Yates:2008:DTO,
author = "Ricardo Baeza-Yates and Aristides Gionis and Flavio P.
Junqueira and Vanessa Murdock and Vassilis Plachouras
and Fabrizio Silvestri",
title = "Design trade-offs for search engine caching",
journal = j-TWEB,
volume = "2",
number = "4",
pages = "20:1--20:??",
month = oct,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1409220.1409223",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In this article we study the trade-offs in designing
efficient caching systems for Web search engines. We
explore the impact of different approaches, such as
static vs. dynamic caching, and caching query results
vs. caching posting lists. Using a query log spanning a
whole year, we explore the limitations of caching and
we demonstrate that caching posting lists can achieve
higher hit rates than caching query answers. We propose
a new algorithm for static caching of posting lists,
which outperforms previous methods. We also study the
problem of finding the optimal way to split the static
cache between answers and posting lists. Finally, we
measure how the changes in the query log influence the
effectiveness of static caching, given our observation
that the distribution of the queries changes slowly
over time. Our results and observations are applicable
to different levels of the data-access hierarchy, for
instance, for a memory/disk layer or a broker/remote
server layer.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Caching; query logs; Web search",
}
@Article{Richardson:2008:LAW,
author = "Matthew Richardson",
title = "Learning about the world through long-term query
logs",
journal = j-TWEB,
volume = "2",
number = "4",
pages = "21:1--21:??",
month = oct,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1409220.1409224",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In this article, we demonstrate the value of long-term
query logs. Most work on query logs to date considers
only short-term (within-session) query information. In
contrast, we show that long-term query logs can be used
to learn about the world we live in. There are many
applications of this that lead not only to improving
the search engine for its users, but also potentially
to advances in other disciplines such as medicine,
sociology, economics, and more. In this article, we
will show how long-term query logs can be used for
these purposes, and that their potential is severely
reduced if the logs are limited to short time horizons.
We show that query effects are long-lasting, provide
valuable information, and might be used to
automatically make medical discoveries, build concept
hierarchies, and generally learn about the sociological
behavior of users. We believe these applications are
only the beginning of what can be done with the
information contained in long-term query logs, and see
this work as a step toward unlocking their potential.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "data mining; knowledge discovery; query logs; user
behavior",
}
@Article{Koutrika:2008:CST,
author = "Georgia Koutrika and Frans Adjie Effendi and
Zolt{\'{}}n Gy{\"o}ngyi and Paul Heymann and Hector
Garcia-Molina",
title = "Combating spam in tagging systems: an evaluation",
journal = j-TWEB,
volume = "2",
number = "4",
pages = "22:1--22:??",
month = oct,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1409220.1409225",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:06 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Tagging systems allow users to interactively annotate
a pool of shared resources using descriptive strings
called {\em tags}. Tags are used to guide users to
interesting resources and help them build communities
that share their expertise and resources. As tagging
systems are gaining in popularity, they become more
susceptible to {\em tag spam\/}: misleading tags that
are generated in order to increase the visibility of
some resources or simply to confuse users. Our goal is
to understand this problem better. In particular, we
are interested in answers to questions such as: How
many malicious users can a tagging system tolerate
before results significantly degrade? What types of
tagging systems are more vulnerable to malicious
attacks? What would be the effort and the impact of
employing a trusted moderator to find bad postings? Can
a system automatically protect itself from spam, for
instance, by exploiting user tag patterns? In a quest
for answers to these questions, we introduce a
framework for modeling tagging systems and user tagging
behavior. We also describe a method for ranking
documents matching a tag based on taggers' reliability.
Using our framework, we study the behavior of existing
approaches under malicious attacks and the impact of a
moderator and our ranking method.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "22",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "bookmarking systems; tag spam; Tagging; tagging
models",
}
@Article{Rattenbury:2009:MEP,
author = "Tye Rattenbury and Mor Naaman",
title = "Methods for extracting place semantics from {Flickr}
tags",
journal = j-TWEB,
volume = "3",
number = "1",
pages = "1:1--1:??",
month = jan,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1462148.1462149",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:15 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We describe an approach for extracting semantics for
tags, unstructured text-labels assigned to resources on
the Web, based on each tag's usage patterns. In
particular, we focus on the problem of extracting place
semantics for tags that are assigned to photos on
Flickr, a popular-photo sharing Web site that supports
location (latitude/longitude) metadata for photos. We
propose the adaptation of two baseline methods,
inspired by well-known burst-analysis techniques, for
the task; we also describe two novel methods, TagMaps
and scale-structure identification. We evaluate the
methods on a subset of Flickr data. We show that our
scale-structure identification method outperforms
existing techniques and that a hybrid approach
generates further improvements (achieving 85\%
precision at 81\% recall). The approach and methods
described in this work can be used in other domains
such as geo-annotated Web pages, where text terms can
be extracted and associated with usage patterns.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "places; semantics; Tagging systems; tags",
}
@Article{Jackson:2009:PBD,
author = "Collin Jackson and Adam Barth and Andrew Bortz and
Weidong Shao and Dan Boneh",
title = "Protecting browsers from {DNS} rebinding attacks",
journal = j-TWEB,
volume = "3",
number = "1",
pages = "2:1--2:??",
month = jan,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1462148.1462150",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:15 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "DNS rebinding attacks subvert the same-origin policy
of browsers, converting them into open network proxies.
Using DNS rebinding, an attacker can circumvent
organizational and personal firewalls, send spam email,
and defraud pay-per-click advertisers. We evaluate the
cost effectiveness of mounting DNS rebinding attacks,
finding that an attacker requires less than \$100 to
hijack 100,000 IP addresses. We analyze defenses to DNS
rebinding attacks, including improvements to the
classic ``DNS pinning,'' and recommend changes to
browser plug-ins, firewalls, and Web servers. Our
defenses have been adopted by plug-in vendors and by a
number of open-source firewall implementations.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "click fraud; DNS; firewall; Same-origin policy; spam",
}
@Article{Bar-Yossef:2009:DCD,
author = "Ziv Bar-Yossef and Idit Keidar and Uri Schonfeld",
title = "Do not crawl in the {DUST}: {Different URLs with
Similar Text}",
journal = j-TWEB,
volume = "3",
number = "1",
pages = "3:1--3:??",
month = jan,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1462148.1462151",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:15 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We consider the problem of DUST: Different URLs with
Similar Text. Such duplicate URLs are prevalent in Web
sites, as Web server software often uses aliases and
redirections, and dynamically generates the same page
from various different URL requests. We present a novel
algorithm, {\em DustBuster}, for uncovering DUST; that
is, for discovering rules that transform a given URL to
others that are likely to have similar content.
DustBuster mines DUST effectively from previous crawl
logs or Web server logs, {\em without\/} examining page
contents. Verifying these rules via sampling requires
fetching few actual Web pages. Search engines can
benefit from information about DUST to increase the
effectiveness of crawling, reduce indexing overhead,
and improve the quality of popularity statistics such
as PageRank.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "antialiasing; crawling; duplicate detection; Search
engines; URL normalization",
}
@Article{Xiao:2009:BSD,
author = "Xiangye Xiao and Qiong Luo and Dan Hong and Hongbo Fu
and Xing Xie and Wei-Ying Ma",
title = "Browsing on small displays by transforming {Web} pages
into hierarchically structured subpages",
journal = j-TWEB,
volume = "3",
number = "1",
pages = "4:1--4:??",
month = jan,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1462148.1462152",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:15 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We propose a new Web page transformation method to
facilitate Web browsing on handheld devices such as
Personal Digital Assistants (PDAs). In our approach, an
original Web page that does not fit on the screen is
transformed into a set of subpages, each of which fits
on the screen. This transformation is done through
slicing the original page into page blocks iteratively,
with several factors considered. These factors include
the size of the screen, the size of each page block,
the number of blocks in each transformed page, the
depth of the tree hierarchy that the transformed pages
form, as well as the semantic coherence between blocks.
We call the tree hierarchy of the transformed pages an
SP-tree. In an SP-tree, an internal node consists of a
textually enhanced thumbnail image with hyperlinks, and
a leaf node is a block extracted from a subpage of the
original Web page. We adaptively adjust the fanout and
the height of the SP-tree so that each thumbnail image
is clear enough for users to read, while at the same
time, the number of clicks needed to reach a leaf page
is few. Through this transformation algorithm, we
preserve the contextual information in the original Web
page and reduce scrolling. We have implemented this
transformation module on a proxy server and have
conducted usability studies on its performance. Our
system achieved a shorter task completion time compared
with that of transformations from the Opera browser in
nine of ten tasks. The average improvement on familiar
pages was 44\%. The average improvement on unfamiliar
pages was 37\%. Subjective responses were positive.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Proxy; slicing tree; small displays; thumbnails; Web
browsing; Web page adaptation",
}
@Article{Gabrilovich:2009:CSQ,
author = "Evgeniy Gabrilovich and Andrei Broder and Marcus
Fontoura and Amruta Joshi and Vanja Josifovski and
Lance Riedel and Tong Zhang",
title = "Classifying search queries using the {Web} as a source
of knowledge",
journal = j-TWEB,
volume = "3",
number = "2",
pages = "5:1--5:??",
month = apr,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1513876.1513877",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:23 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We propose a methodology for building a robust query
classification system that can identify thousands of
query classes, while dealing in real time with the
query volume of a commercial Web search engine. We use
a pseudo relevance feedback technique: given a query,
we determine its topic by classifying the Web search
results retrieved by the query. Motivated by the needs
of search advertising, we primarily focus on rare
queries, which are the hardest from the point of view
of machine learning, yet in aggregate account for a
considerable fraction of search engine traffic.
Empirical evaluation confirms that our methodology
yields a considerably higher classification accuracy
than previously reported. We believe that the proposed
methodology will lead to better matching of online ads
to rare queries and overall to a better user
experience.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Pseudo relevance feedback; query classification; Web
search",
}
@Article{Reay:2009:LSE,
author = "Ian Reay and Scott Dick and James Miller",
title = "A large-scale empirical study of {P3P} privacy
policies: {Stated} actions vs. legal obligations",
journal = j-TWEB,
volume = "3",
number = "2",
pages = "6:1--6:??",
month = apr,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1513876.1513878",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:23 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Numerous studies over the past ten years have shown
that concern for personal privacy is a major impediment
to the growth of e-commerce. These concerns are so
serious that most if not all consumer watchdog groups
have called for some form of privacy protection for
Internet users. In response, many nations around the
world, including all European Union nations, Canada,
Japan, and Australia, have enacted national legislation
establishing mandatory safeguards for personal privacy.
However, recent evidence indicates that Web sites might
not be adhering to the requirements of this
legislation. The goal of this study is to examine the
posted privacy policies of Web sites, and compare these
statements to the legal mandates under which the Web
sites operate. We harvested all available P3P (Platform
for Privacy Preferences Protocol) documents from the
100,000 most popular Web sites (over 3,000 full
policies, and another 3,000 compact policies). This
allows us to undertake an automated analysis of
adherence to legal mandates on Web sites that most
impact the average Internet user. Our findings show
that Web sites generally do not even claim to follow
all the privacy-protection mandates in their legal
jurisdiction (we do not examine actual practice, only
posted policies). Furthermore, this general statement
appears to be true for every jurisdiction with privacy
laws and any significant number of P3P policies,
including European Union nations, Canada, Australia,
and Web sites in the USA Safe Harbor program.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "electronic commerce; legislation and enforcement; P3P;
Privacy protection",
}
@Article{Dourisboure:2009:ECD,
author = "Yon Dourisboure and Filippo Geraci and Marco
Pellegrini",
title = "Extraction and classification of dense implicit
communities in the {Web} graph",
journal = j-TWEB,
volume = "3",
number = "2",
pages = "7:1--7:??",
month = apr,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1513876.1513879",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Fri Apr 24 18:18:23 MDT 2009",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The World Wide Web (WWW) is rapidly becoming important
for society as a medium for sharing data, information,
and services, and there is a growing interest in tools
for understanding collective behavior and emerging
phenomena in the WWW. In this article we focus on the
problem of searching and classifying {\em
communities\/} in the Web. Loosely speaking a community
is a group of pages related to a common interest. More
formally, communities have been associated in the
computer science literature with the existence of a
locally dense subgraph of the Web graph (where Web
pages are nodes and hyperlinks are arcs of the Web
graph). The core of our contribution is a new scalable
algorithm for finding relatively dense subgraphs in
massive graphs. We apply our algorithm on Web graphs
built on three publicly available large crawls of the
Web (with raw sizes up to 120M nodes and 1G arcs). The
effectiveness of our algorithm in finding dense
subgraphs is demonstrated experimentally by embedding
artificial communities in the Web graph and counting
how many of these are blindly found. Effectiveness
increases with the size and density of the communities:
it is close to 100\% for communities of thirty nodes or
more (even at low density). It is still about 80\% even
for communities of twenty nodes with density over 50\%
of the arcs present. At the lower extremes the
algorithm catches 35\% of dense communities made of ten
nodes. We also develop some sufficient conditions for
the detection of a community under some local graph
models and not-too-restrictive hypotheses. We complete
our {\em Community Watch\/} system by clustering the
communities found in the Web graph into homogeneous
groups by topic and labeling each group by
representative keywords.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "communities; detection of dense subgraph; Web graph",
}
@Article{Lee:2009:ISB,
author = "Hsin-Tsang Lee and Derek Leonard and Xiaoming Wang and
Dmitri Loguinov",
title = "{IRLbot}: {Scaling} to 6 billion pages and beyond",
journal = j-TWEB,
volume = "3",
number = "3",
pages = "8:1--8:??",
month = jun,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1541822.1541823",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:38 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This article shares our experience in designing a Web
crawler that can download billions of pages using a
single-server implementation and models its
performance. We first show that current crawling
algorithms cannot effectively cope with the sheer
volume of URLs generated in large crawls, highly
branching spam, legitimate multimillion-page blog
sites, and infinite loops created by server-side
scripts. We then offer a set of techniques for dealing
with these issues and test their performance in an
implementation we call IRLbot. In our recent experiment
that lasted 41 days, IRLbot running on a single server
successfully crawled 6.3 billion valid HTML pages (7.6
billion connection requests) and sustained an average
download rate of 319 mb/s (1,789 pages/s). Unlike our
prior experiments with algorithms proposed in related
work, this version of IRLbot did not experience any
bottlenecks and successfully handled content from over
117 million hosts, parsed out 394 billion links, and
discovered a subset of the Web graph with 41 billion
unique nodes.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "crawling; IRLbot; large scale",
}
@Article{Tappenden:2009:CDS,
author = "Andrew F. Tappenden and James Miller",
title = "Cookies: a deployment study and the testing
implications",
journal = j-TWEB,
volume = "3",
number = "3",
pages = "9:1--9:??",
month = jun,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1541822.1541824",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:38 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The results of an extensive investigation of cookie
deployment amongst 100,000 Internet sites are
presented. Cookie deployment is found to be approaching
universal levels and hence there exists an associated
need for relevant Web and software engineering
processes, specifically testing strategies which
actively consider cookies. The semi-automated
investigation demonstrates that over two-thirds of the
sites studied deploy cookies. The investigation
specifically examines the use of first-party,
third-party, sessional, and persistent cookies within
Web-based applications, identifying the presence of a
P3P policy and dynamic Web technologies as major
predictors of cookie usage. The results are juxtaposed
with the lack of testing strategies present in the
literature. A number of real-world examples, including
two case studies are presented, further accentuating
the need for comprehensive testing strategies for
Web-based applications. The use of antirandom test case
generation is explored with respect to the testing
issues discussed. Finally, a number of seeding vectors
are presented, providing a basis for testing cookies
within Web-based applications.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Cookies; Internet browser; software testing; Web
engineering; Web technologies",
}
@Article{Comuzzi:2009:FQB,
author = "Marco Comuzzi and Barbara Pernici",
title = "A framework for {QoS}-based {Web} service
contracting",
journal = j-TWEB,
volume = "3",
number = "3",
pages = "10:1--10:??",
month = jun,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1541822.1541825",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:38 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The extensive adoption of Web service-based
applications in dynamic business scenarios, such as
on-demand computing or highly reconfigurable virtual
enterprises, advocates for methods and tools for the
management of Web service nonfunctional aspects, such
as Quality of Service (QoS). Concerning contracts on
Web service QoS, the literature has mostly focused on
the contract definition and on mechanisms for contract
enactment, such as the monitoring of the satisfaction
of negotiated QoS guarantees. In this context, this
article proposes a framework for the automation of the
Web service contract specification and establishment.
An extensible model for defining both domain-dependent
and domain-independent Web service QoS dimensions and a
method for the automation of the contract establishment
phase are proposed. We describe a matchmaking algorithm
for the ranking of functionally equivalent services,
which orders services on the basis of their ability to
fulfill the service requestor requirements, while
maintaining the price below a specified budget. We also
provide an algorithm for the configuration of the
negotiable part of the QoS Service-Level Agreement
(SLA), which is used to configure the agreement with
the top-ranked service identified in the matchmaking
phase. Experimental results show that, in a utility
theory perspective, the contract establishment phase
leads to efficient outcomes. We envision two advanced
application scenarios for the Web service contracting
framework proposed in this article. First, it can be
used to enhance Web services self-healing properties in
reaction to QoS-related service failures; second, it
can be exploited in process optimization for the online
reconfiguration of candidate Web services QoS SLAs.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "matchmaking; negotiation; QoS; service selection; SLA;
Web service",
}
@Article{Pilioura:2009:UPD,
author = "Thomi Pilioura and Aphrodite Tsalgatidou",
title = "Unified publication and discovery of semantic {Web}
services",
journal = j-TWEB,
volume = "3",
number = "3",
pages = "11:1--11:??",
month = jun,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1541822.1541826",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:38 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The challenge of publishing and discovering Web
services has recently received lots of attention.
Various solutions to this problem have been proposed
which, apart from their offered advantages, suffer the
following disadvantages: (i) most of them are
syntactic-based, leading to poor precision and recall,
(ii) they are not scalable to large numbers of
services, and (iii) they are incompatible, thus
yielding in cumbersome service publication and
discovery. This article presents the principles, the
functionality, and the design of PYRAMID-S which
addresses these disadvantages by providing a scalable
framework for unified publication and discovery of
semantically enhanced services over heterogeneous
registries. PYRAMID-S uses a hybrid peer-to-peer
topology to organize Web service registries based on
domains. In such a topology, each Registry retains its
autonomy, meaning that it can use the publication and
discovery mechanisms as well as the ontology of its
choice. The viability of this approach is demonstrated
through the implementation and experimental analysis of
a prototype.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "evaluation; PYRAMID-S; scalable; semantic Web
services; unified; Web service discovery; Web service
publication",
}
@Article{Golbeck:2009:TNP,
author = "Jennifer Golbeck",
title = "Trust and nuanced profile similarity in online social
networks",
journal = j-TWEB,
volume = "3",
number = "4",
pages = "12:1--12:??",
month = sep,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1594173.1594174",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:43 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Singh:2009:SSO,
author = "Aameek Singh and Mudhakar Srivatsa and Ling Liu",
title = "Search-as-a-service: {Outsourced} search over
outsourced storage",
journal = j-TWEB,
volume = "3",
number = "4",
pages = "13:1--13:??",
month = sep,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1594173.1594175",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:43 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Robu:2009:ECS,
author = "Valentin Robu and Harry Halpin and Hana Shepherd",
title = "Emergence of consensus and shared vocabularies in
collaborative tagging systems",
journal = j-TWEB,
volume = "3",
number = "4",
pages = "14:1--14:??",
month = sep,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1594173.1594176",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:43 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zheng:2010:UTM,
author = "Yu Zheng and Yukun Chen and Quannan Li and Xing Xie
and Wei-Ying Ma",
title = "Understanding transportation modes based on {GPS} data
for {Web} applications",
journal = j-TWEB,
volume = "4",
number = "1",
pages = "1:1--1:??",
month = jan,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1658373.1658374",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:45 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Li:2010:DSO,
author = "Guoli Li and Vinod Muthusamy and Hans-Arno Jacobsen",
title = "A distributed service-oriented architecture for
business process execution",
journal = j-TWEB,
volume = "4",
number = "1",
pages = "2:1--2:??",
month = jan,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1658373.1658375",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:45 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Montali:2010:DSV,
author = "Marco Montali and Maja Pesic and Wil M. P. van der
Aalst and Federico Chesani and Paola Mello and Sergio
Storari",
title = "Declarative specification and verification of service
choreographies",
journal = j-TWEB,
volume = "4",
number = "1",
pages = "3:1--3:??",
month = jan,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1658373.1658376",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Mar 16 09:28:45 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Almishari:2010:APD,
author = "Mishari Almishari and Xiaowei Yang",
title = "Ads-portal domains: {Identification} and
measurements",
journal = j-TWEB,
volume = "4",
number = "2",
pages = "4:1--4:??",
month = apr,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1734200.1734201",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:32 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "An ads-portal domain refers to a Web domain that shows
only advertisements, served by a third-party
advertisement syndication service, in the form of ads
listing. We develop a machine-learning-based classifier
to identify ads-portal domains, which has 96\%
accuracy. We use this classifier to measure the
prevalence of ads-portal domains on the Internet.
Surprisingly, 28.3/25\% of the (two-level) {\tt *.com}
/{\tt *.net} web domains are ads-portal domains. Also,
41/39.8\% of {\tt *.com} /{\tt *.net} ads-portal
domains are typos of well-known domains, also known as
typo-squatting domains. In addition, we use the
classifier along with DNS trace files to estimate how
often Internet users visit ads-portal domains. It turns
out that $ \approx 5 \% $ of the two-level {\tt *.com},
{\tt *.net}, {\tt *.org}, {\tt *.biz} and {\tt *.info}
web domains on the traces are ads-portal domains and $
\approx 50 \% $ of these accessed ads-portal domains
are typos. These numbers show that ads-portal domains
and typo-squatting ads-portal domains are prevalent on
the Internet and successful in attracting many visits.
Our classifier represents a step towards better
categorizing the web documents. It can also be helpful
to search engines ranking algorithms, helpful in
identifying web spams that redirects to ads-portal
domains, and used to discourage access to
typo-squatting ads-portal domains.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Ads-portal; advertisement syndication; data mining;
parked domain; parking service; Web characterization",
}
@Article{Jurca:2010:RIB,
author = "Radu Jurca and Florent Garcin and Arjun Talwar and Boi
Faltings",
title = "Reporting incentives and biases in online review
forums",
journal = j-TWEB,
volume = "4",
number = "2",
pages = "5:1--5:??",
month = apr,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1734200.1734202",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:32 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Online reviews have become increasingly popular as a
way to judge the quality of various products and
services. However, recent work demonstrates that the
absence of reporting incentives leads to a biased set
of reviews that may not reflect the true quality. In
this paper, we investigate underlying factors that
influence users when reporting feedback. In particular,
we study both reporting incentives and reporting biases
observed in a widely used review forum, the Tripadvisor
Web site. We consider three sources of information:
first, the numerical ratings left by the user for
different aspects of quality; second, the textual
comment accompanying a review; third, the patterns in
the time sequence of reports. We first show that groups
of users who discuss a certain feature at length are
more likely to agree in their ratings. Second, we show
that users are more motivated to give feedback when
they perceive a greater risk involved in a transaction.
Third, a user's rating partly reflects the difference
between true quality and prior expectation of quality,
as inferred from previous reviews. We finally observe
that because of these biases, when averaging review
scores there are strong differences between the mean
and the median. We speculate that the median may be a
better way to summarize the ratings.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Online reviews; reputation mechanisms",
}
@Article{Vlachos:2010:ODB,
author = "Michail Vlachos and Suleyman S. Kozat and Philip S.
Yu",
title = "Optimal distance bounds for fast search on compressed
time-series query logs",
journal = j-TWEB,
volume = "4",
number = "2",
pages = "6:1--6:??",
month = apr,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1734200.1734203",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:32 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Consider a database of time-series, where each
datapoint in the series records the total number of
users who asked for a specific query at an Internet
search engine. Storage and analysis of such logs can be
very beneficial for a search company from multiple
perspectives. First, from a data organization
perspective, because query Weblogs capture important
trends and statistics, they can help enhance and
optimize the search experience (keyword recommendation,
discovery of news events). Second, Weblog data can
provide an important polling mechanism for the
microeconomic aspects of a search engine, since they
can facilitate and promote the advertising facet of the
search engine (understand what users request and when
they request it).\par
Due to the sheer amount of time-series Weblogs,
manipulation of the logs in a compressed form is an
impeding necessity for fast data processing and compact
storage requirements. Here, we explicate how to compute
the lower and upper distance bounds on the time-series
logs when working directly on their compressed form.
Optimal distance estimation means tighter bounds,
leading to better candidate selection/elimination and
ultimately faster search performance. Our derivation of
the optimal distance bounds is based on the careful
analysis of the problem using optimization principles.
The experimental evaluation suggests a clear
performance advantage of the proposed method, compared
to previous compression/search techniques. The
presented method results in a 10--30\% improvement on
distance estimations, which in turn leads to 25--80\%
improvement on the search performance.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Fraternali:2010:ERI,
author = "Piero Fraternali and Sara Comai and Alessandro Bozzon
and Giovanni Toffetti Carughi",
title = "Engineering rich {Internet} applications with a
model-driven approach",
journal = j-TWEB,
volume = "4",
number = "2",
pages = "7:1--7:??",
month = apr,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1734200.1734204",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:32 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Rich Internet Applications (RIAs) have introduced
powerful novel functionalities into the Web
architecture, borrowed from client-server and desktop
applications. The resulting platforms allow designers
to improve the user's experience, by exploiting
client-side data and computation, bidirectional
client-server communication, synchronous and
asynchronous events, and rich interface widgets.
However, the rapid evolution of RIA technologies
challenges the Model-Driven Development methodologies
that have been successfully applied in the past decade
to traditional Web solutions. This paper illustrates an
evolutionary approach for incorporating a wealth of RIA
features into an existing Web engineering methodology
and notation. The experience demonstrates that it is
possible to model RIA application requirements at a
high-level using a platform-independent notation, and
generate the client-side and server-side code
automatically. The resulting approach is evaluated in
terms of expressive power, ease of use, and
implementability.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "information interfaces and presentation; information
storage and retrieval; model-driven development; Rich
Internet applications; Web engineering",
}
@Article{Xiao:2010:LSS,
author = "Xiangye Xiao and Qiong Luo and Zhisheng Li and Xing
Xie and Wei-Ying Ma",
title = "A large-scale study on map search logs",
journal = j-TWEB,
volume = "4",
number = "3",
pages = "8:1--8:??",
month = jul,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1806916.1806917",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:40 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Map search engines, such as Google Maps, Yahoo! Maps,
and Microsoft Live Maps, allow users to explicitly
specify a target geographic location, either in
keywords or on the map, and to search businesses,
people, and other information of that location. In this
article, we report a first study on a million-entry map
search log. We identify three key attributes of a map
search record --- the keyword query, the target
location and the user location, and examine the
characteristics of these three dimensions separately as
well as the associations between them. Comparing our
results with those previously reported on logs of
general search engines and mobile search engines,
including those for geographic queries, we discover the
following unique features of map search: (1) People use
longer queries and modify queries more frequently in a
session than in general search and mobile search;
People view fewer result pages per query than in
general search; (2) The popular query topics in map
search are different from those in general search and
mobile search; (3) The target locations in a session
change within 50 kilometers for almost 80\% of the
sessions; (4) Queries, search target locations and user
locations (both at the city level) all follow the power
law distribution; (5) One third of queries are issued
for target locations within 50 kilometers from the user
locations; (6) The distribution of a query over target
locations appears to follow the geographic location of
the queried entity.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "local search; log analysis; Map search; query
categorization; search interface; user behavior",
}
@Article{Malak:2010:MWQ,
author = "Ghazwa Malak and Houari Sahraoui and Linda Badri and
Mourad Badri",
title = "Modeling {Web} quality using a probabilistic approach:
an empirical validation",
journal = j-TWEB,
volume = "4",
number = "3",
pages = "9:1--9:??",
month = jul,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1806916.1806918",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:40 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Web-based applications are software systems that
continuously evolve to meet users' needs and to adapt
to new technologies. Assuring their quality is then a
difficult, but essential task. In fact, a large number
of factors can affect their quality. Considering these
factors and their interaction involves managing
uncertainty and subjectivity inherent to this kind of
applications. In this article, we present a
probabilistic approach for building Web quality models
and the associated assessment method. The proposed
approach is based on Bayesian Networks. A model is
built following a four-step process consisting in
collecting quality characteristics, refining them,
building a model structure, and deriving the model
parameters.\par
The feasibility of the approach is illustrated on the
important quality characteristic of {\em Navigability
design}. To validate the produced model, we conducted
an experimental study with 20 subjects and 40 web
pages. The results obtained show that the scores given
by the used model are strongly correlated with
navigability as perceived and experienced by the
users.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Bayesian networks; Navigability design; probabilistic
approach; quality evaluation; Web applications",
}
@Article{Poblete:2010:PPQ,
author = "Barbara Poblete and Myra Spiliopoulou and Ricardo
Baeza-Yates",
title = "Privacy-preserving query log mining for business
confidentiality protection",
journal = j-TWEB,
volume = "4",
number = "3",
pages = "10:1--10:??",
month = jul,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1806916.1806919",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:40 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We introduce the concern of confidentiality protection
of business information for the publication of search
engine query logs and derived data. We study business
confidentiality, as the protection of nonpublic data
from institutions, such as companies and people in the
public eye. In particular, we relate this concern to
the involuntary exposure of confidential Web site
information, and we transfer this problem into the
field of privacy-preserving data mining. We
characterize the possible adversaries interested in
disclosing Web site confidential data and the attack
strategies that they could use. These attacks are based
on different vulnerabilities found in query log for
which we present several anonymization heuristics to
prevent them. We perform an experimental evaluation to
estimate the remaining utility of the log after the
application of our anonymization techniques. Our
experimental results show that a query log can be
anonymized against these specific attacks while
retaining a significant volume of useful data.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Privacy preservation; queries; query log publication;
Web sites",
}
@Article{Consens:2010:EXW,
author = "Mariano P. Consens and Ren{\'e}e J. Miller and Flavio
Rizzolo and Alejandro A. Vaisman",
title = "Exploring {XML} {Web} collections with {DescribeX}",
journal = j-TWEB,
volume = "4",
number = "3",
pages = "11:1--11:??",
month = jul,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1806916.1806920",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:40 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "As Web applications mature and evolve, the nature of
the semistructured data that drives these applications
also changes. An important trend is the need for
increased flexibility in the structure of Web
documents. Hence, applications cannot rely solely on
schemas to provide the complex knowledge needed to
visualize, use, query and manage documents. Even when
XML Web documents are valid with regard to a schema,
the actual structure of such documents may exhibit
significant variations across collections for several
reasons: the schema may be very lax (e.g., RSS feeds),
the schema may be large and different subsets of it may
be used in different documents (e.g., industry
standards like UBL), or open content models may allow
arbitrary schemas to be mixed (e.g., RSS extensions
like those used for podcasting). For these reasons,
many applications that incorporate XPath queries to
process a large Web document collection require an
understanding of the actual structure present in the
collection, and not just the schema.\par
To support modern Web applications, we introduce
DescribeX, a powerful framework that is capable of
describing complex XML summaries of Web collections.
DescribeX supports the construction of heterogeneous
summaries that can be declaratively defined and refined
by means of axis path regular expression (AxPREs).
AxPREs provide the flexibility necessary for
declaratively defining complex mappings between
instance nodes (in the documents) and summary nodes.
These mappings are capable of expressing order and
cardinality, among other properties, which can
significantly help in the understanding of the
structure of large collections of XML documents and
enhance the performance of Web applications over these
collections. DescribeX captures most summary proposals
in the literature by providing (for the first time) a
common declarative definition for them. Experimental
results demonstrate the scalability of DescribeX
summary operations (summary creation, as well as
refinement and stabilization, two key enablers for
tailoring summaries) on multi-gigabyte Web
collections.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Semistructured data; structural summaries; XML;
XPath",
}
@Article{Adams:2010:DLS,
author = "Brett Adams and Dinh Phung and Svetha Venkatesh",
title = "Discovery of latent subcommunities in a blog's
readership",
journal = j-TWEB,
volume = "4",
number = "3",
pages = "12:1--12:??",
month = jul,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1806916.1806921",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Sat Aug 14 15:42:40 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The blogosphere has grown to be a mainstream forum of
social interaction as well as a commercially attractive
source of information and influence. Tools are needed
to better understand how communities that adhere to
individual blogs are constituted in order to facilitate
new personal, socially-focused browsing paradigms, and
understand how blog content is consumed, which is of
interest to blog authors, big media, and search. We
present a novel approach to blog subcommunity
characterization by modeling individual blog readers
using mixtures of an extension to the LDA family that
jointly models phrases and time, Ngram Topic over Time
(NTOT), and cluster with a number of similarity
measures using Affinity Propagation. We experiment with
two datasets: a small set of blogs whose authors
provide feedback, and a set of popular, highly
commented blogs, which provide indicators of algorithm
scalability and interpretability without prior
knowledge of a given blog. The results offer useful
insight to the blog authors about their commenting
community, and are observed to offer an integrated
perspective on the topics of discussion and members
engaged in those discussions for unfamiliar blogs. Our
approach also holds promise as a component of solutions
to related problems, such as online entity resolution
and role discovery.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "affinity propagation; Blog; topic models; Web
communities",
}
@Article{Kiciman:2010:APR,
author = "Emre Kiciman and Benjamin Livshits",
title = "{AjaxScope}: a Platform for Remotely Monitoring the
Client-Side Behavior of {Web 2.0} Applications",
journal = j-TWEB,
volume = "4",
number = "4",
pages = "13:1--13:??",
month = sep,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1841909.1841910",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Nov 23 12:48:27 MST 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bex:2010:LDR,
author = "Geert Jan Bex and Wouter Gelade and Frank Neven and
Stijn Vansummeren",
title = "Learning Deterministic Regular Expressions for the
Inference of Schemas from {XML} Data",
journal = j-TWEB,
volume = "4",
number = "4",
pages = "14:1--14:??",
month = sep,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1841909.1841911",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Nov 23 12:48:27 MST 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bailey:2010:MHQ,
author = "Peter Bailey and Ryen W. White and Han Liu and
Giridhar Kumaran",
title = "Mining Historic Query Trails to Label Long and Rare
Search Engine Queries",
journal = j-TWEB,
volume = "4",
number = "4",
pages = "15:1--15:??",
month = sep,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1841909.1841912",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Nov 23 12:48:27 MST 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Claude:2010:FCW,
author = "Francisco Claude and Gonzalo Navarro",
title = "Fast and Compact {Web} Graph Representations",
journal = j-TWEB,
volume = "4",
number = "4",
pages = "16:1--16:??",
month = sep,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1841909.1841913",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Nov 23 12:48:27 MST 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Swaminathan:2010:RRM,
author = "Ashwin Swaminathan and Renan G. Cattelan and Ydo
Wexler and Cherian V. Mathew and Darko Kirovski",
title = "Relating Reputation and Money in Online Markets",
journal = j-TWEB,
volume = "4",
number = "4",
pages = "17:1--17:??",
month = sep,
year = "2010",
CODEN = "????",
DOI = "https://doi.org/10.1145/1841909.1841914",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Nov 23 12:48:27 MST 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Riedl:2011:ISI,
author = "John Riedl and Barry Smyth",
title = "Introduction to special issue on recommender systems",
journal = j-TWEB,
volume = "5",
number = "1",
pages = "1:1--1:??",
month = feb,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1921591.1921592",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Mon Mar 28 11:56:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cacheda:2011:CCF,
author = "Fidel Cacheda and V{\'\i}ctor Carneiro and Diego
Fern{\'a}ndez and Vreixo Formoso",
title = "Comparison of collaborative filtering algorithms:
Limitations of current techniques and proposals for
scalable, high-performance recommender systems",
journal = j-TWEB,
volume = "5",
number = "1",
pages = "2:1--2:??",
month = feb,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1921591.1921593",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Mon Mar 28 11:56:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Umyarov:2011:UEA,
author = "Akhmed Umyarov and Alexander Tuzhilin",
title = "Using external aggregate ratings for improving
individual recommendations",
journal = j-TWEB,
volume = "5",
number = "1",
pages = "3:1--3:??",
month = feb,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1921591.1921594",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Mon Mar 28 11:56:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Song:2011:ATR,
author = "Yang Song and Lu Zhang and C. Lee Giles",
title = "Automatic tag recommendation algorithms for social
recommender systems",
journal = j-TWEB,
volume = "5",
number = "1",
pages = "4:1--4:??",
month = feb,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1921591.1921595",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Mon Mar 28 11:56:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zheng:2011:RFL,
author = "Yu Zheng and Lizhu Zhang and Zhengxin Ma and Xing Xie
and Wei-Ying Ma",
title = "Recommending friends and locations based on individual
location history",
journal = j-TWEB,
volume = "5",
number = "1",
pages = "5:1--5:??",
month = feb,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1921591.1921596",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Mon Mar 28 11:56:06 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wu:2011:TDQ,
author = "Mingfang Wu and Falk Scholer and Andrew Turpin",
title = "Topic Distillation with Query-Dependent Link
Connections and Page Characteristics",
journal = j-TWEB,
volume = "5",
number = "2",
pages = "6:1--6:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1961659.1961660",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Jun 7 18:44:15 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Hurley:2011:HBP,
author = "John Hurley and Emi Garcia-Palacios and Sakir Sezer",
title = "Host-Based {P2P} Flow Identification and Use in
Real-Time",
journal = j-TWEB,
volume = "5",
number = "2",
pages = "7:1--7:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1961659.1961661",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Jun 7 18:44:15 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Mitra:2011:CWB,
author = "Siddharth Mitra and Mayank Agrawal and Amit Yadav and
Niklas Carlsson and Derek Eager and Anirban Mahanti",
title = "Characterizing {Web}-Based Video Sharing Workloads",
journal = j-TWEB,
volume = "5",
number = "2",
pages = "8:1--8:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1961659.1961662",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Jun 7 18:44:15 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Ozcan:2011:CAS,
author = "Rifat Ozcan and Ismail Sengor Altingovde and
{\"O}zg{\"u}r Ulusoy",
title = "Cost-Aware Strategies for Query Result Caching in
{Web} Search Engines",
journal = j-TWEB,
volume = "5",
number = "2",
pages = "9:1--9:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1961659.1961663",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Jun 7 18:44:15 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Valderas:2011:SRS,
author = "Pedro Valderas and Vicente Pelechano",
title = "A Survey of Requirements Specification in Model-Driven
Development of {Web} Applications",
journal = j-TWEB,
volume = "5",
number = "2",
pages = "10:1--10:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1961659.1961664",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Jun 7 18:44:15 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Grier:2011:DIO,
author = "Chris Grier and Shuo Tang and Samuel T. King",
title = "Designing and Implementing the {OP} and {OP2} {Web}
Browsers",
journal = j-TWEB,
volume = "5",
number = "2",
pages = "11:1--11:??",
month = may,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1961659.1961665",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Tue Jun 7 18:44:15 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Koutsonikola:2011:CDL,
author = "Vassiliki Koutsonikola and Athena Vakali",
title = "A Clustering-Driven {LDAP} Framework",
journal = j-TWEB,
volume = "5",
number = "3",
pages = "12:1--12:??",
month = jul,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1993053.1993054",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Thu Aug 18 13:57:29 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Paci:2011:AAC,
author = "Federica Paci and Massimo Mecella and Mourad Ouzzani
and Elisa Bertino",
title = "{ACConv} -- An Access Control Model for Conversational
{Web} Services",
journal = j-TWEB,
volume = "5",
number = "3",
pages = "13:1--13:??",
month = jul,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1993053.1993055",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Thu Aug 18 13:57:29 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zeginis:2011:CDR,
author = "Dimitris Zeginis and Yannis Tzitzikas and Vassilis
Christophides",
title = "On Computing Deltas of {RDF/S} Knowledge Bases",
journal = j-TWEB,
volume = "5",
number = "3",
pages = "14:1--14:??",
month = jul,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1993053.1993056",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Thu Aug 18 13:57:29 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Baykan:2011:CSF,
author = "Eda Baykan and Monika Henzinger and Ludmila Marian and
Ingmar Weber",
title = "A Comprehensive Study of Features and Algorithms for
{URL}-Based Topic Classification",
journal = j-TWEB,
volume = "5",
number = "3",
pages = "15:1--15:??",
month = jul,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1993053.1993057",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Thu Aug 18 13:57:29 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Tuchinda:2011:BMD,
author = "Rattapoom Tuchinda and Craig A. Knoblock and Pedro
Szekely",
title = "Building Mashups by Demonstration",
journal = j-TWEB,
volume = "5",
number = "3",
pages = "16:1--16:??",
month = jul,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/1993053.1993058",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
bibdate = "Thu Aug 18 13:57:29 MDT 2011",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Alzoubi:2011:PAA,
author = "Hussein A. Alzoubi and Seungjoon Lee and Michael
Rabinovich and Oliver Spatscheck and Jacobus {Van Der
Merwe}",
title = "A Practical Architecture for an {Anycast CDN}",
journal = j-TWEB,
volume = "5",
number = "4",
pages = "17:1--17:??",
month = oct,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2019643.2019644",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:40 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "IP Anycast has many attractive features for any
service that involve the replication of multiple
instances across the Internet. IP Anycast allows
multiple instances of the same service to be
`naturally' discovered, and requests for this service
to be delivered to the closest instance. However, while
briefly considered as an enabler for content delivery
networks (CDNs) when they first emerged, IP Anycast was
deemed infeasible in that environment. The main reasons
for this decision were the lack of load awareness of IP
Anycast and unwanted side effects of Internet routing
changes on the IP Anycast mechanism. In this article we
re-evaluate IP Anycast for CDNs by proposing a
load-aware IP Anycast CDN architecture. Our
architecture is prompted by recent developments in
route control technology, as well as better
understanding of the behavior of IP Anycast in
operational settings. Our architecture makes use of
route control mechanisms to take server and network
load into account to realize load-aware Anycast. We
show that the resulting redirection requirements can be
formulated as a Generalized Assignment Problem and
present practical algorithms that address these
requirements while at the same time limiting connection
disruptions that plague regular IP Anycast. We evaluate
our algorithms through trace based simulation using
traces obtained from a production CDN network.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bar-Yossef:2011:ESE,
author = "Ziv Bar-Yossef and Maxim Gurevich",
title = "Efficient Search Engine Measurements",
journal = j-TWEB,
volume = "5",
number = "4",
pages = "18:1--18:??",
month = oct,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2019643.2019645",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:40 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We address the problem of externally measuring
aggregate functions over documents indexed by search
engines, like corpus size, index freshness, and density
of duplicates in the corpus. State of the art
estimators for such quantities [Bar-Yossef and Gurevich
2008b; Broder et al. 2006] are biased due to inaccurate
approximation of the so called `document degrees'. In
addition, the estimators in Bar-Yossef and Gurevich
[2008b] are quite costly, due to their reliance on
rejection sampling. We present new estimators that are
able to overcome the bias introduced by approximate
degrees. Our estimators are based on a careful
implementation of an approximate importance sampling
procedure. Comprehensive theoretical and empirical
analysis of the estimators demonstrates that they have
essentially no bias even in situations where document
degrees are poorly approximated. By avoiding the costly
rejection sampling approach, our new importance
sampling estimators are significantly more efficient
than the estimators proposed in Bar-Yossef and Gurevich
[2008b]. Furthermore, building on an idea from Broder
et al. [2006], we discuss Rao-Blackwellization as a
generic method for reducing variance in search engine
estimators. We show that Rao-Blackwellizing our
estimators results in performance improvements, without
compromising accuracy.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Gill:2011:COU,
author = "Phillipa Gill and Martin Arlitt and Niklas Carlsson
and Anirban Mahanti and Carey Williamson",
title = "Characterizing Organizational Use of {Web}-Based
Services: Methodology, Challenges, Observations, and
Insights",
journal = j-TWEB,
volume = "5",
number = "4",
pages = "19:1--19:??",
month = oct,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2019643.2019646",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:40 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Today's Web provides many different functionalities,
including communication, entertainment, social
networking, and information retrieval. In this article,
we analyze traces of HTTP activity from a large
enterprise and from a large university to identify and
characterize Web-based service usage. Our work provides
an initial methodology for the analysis of Web-based
services. While it is nontrivial to identify the
classes, instances, and providers for each transaction,
our results show that most of the traffic comes from a
small subset of providers, which can be classified
manually. Furthermore, we assess both qualitatively and
quantitatively how the Web has evolved over the past
decade, and discuss the implications of these
changes.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Singla:2011:CBC,
author = "Adish Singla and Ingmar Weber",
title = "Camera Brand Congruence and Camera Model Propagation
in the {Flickr} Social Graph",
journal = j-TWEB,
volume = "5",
number = "4",
pages = "20:1--20:??",
month = oct,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2019643.2019647",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:40 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Given that my friends on Flickr use cameras of brand
X, am I more likely to also use a camera of brand X?
Given that one of these friends changes her brand, am I
likely to do the same? Do new camera models pop up
uniformly in the friendship graph? Or do early adopters
then `convert' their friends? Which factors influence
the conversion probability of a user? These are the
kind of questions addressed in this work. Direct
applications involve personalized advertising in social
networks. For our study, we crawled a complete
connected component of the Flickr friendship graph with
a total of 67M edges and 3.9M users. 1.2M of these
users had at least one public photograph with valid
model metadata, which allowed us to assign camera
brands and models to users and time slots. Similarly,
we used, where provided in a user's profile,
information about a user's geographic location and the
groups joined on Flickr. Concerning brand congruence,
our main findings are the following. First, a pair of
friends on Flickr has a higher probability of being
congruent, that is, using the same brand, compared to
two random users (27\% vs. 19\%). Second, the degree of
congruence goes up for pairs of friends (i) in the same
country (29\%), (ii) who both only have very few
friends (30\%), and (iii) with a very high cliqueness
(38\%). Third, given that a user changes her camera
model between March-May 2007 and March-May 2008, high
cliqueness friends are more likely than random users to
do the same (54\% vs. 48\%). Fourth, users using
high-end cameras are far more loyal to their brand than
users using point-and-shoot cameras, with a probability
of staying with the same brand of 60\% vs 33\%, given
that a new camera is bought. Fifth, these `expert'
users' brand congruence reaches 66\% for high
cliqueness friends. All these differences are
statistically significant at 1\%. As for the
propagation of new models in the friendship graph, we
observe the following. First, the growth of connected
components of users converted to a particular, new
camera model differs distinctly from random growth.
Second, the decline of dissemination of a particular
model is close to random decline. This illustrates that
users influence their friends to change to a particular
new model, rather than from a particular old model.
Third, having many converted friends increases the
probability of the user to convert herself. Here
differences between friends from the same or from
different countries are more pronounced for
point-and-shoot than for digital single-lens reflex
users. Fourth, there was again a distinct difference
between arbitrary friends and high cliqueness friends
in terms of prediction quality for conversion.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Curlango-Rosas:2011:SSA,
author = "Cecilia Curlango-Rosas and Gregorio A. Ponce and
Gabriel A. Lopez-Morteo",
title = "A Specialized Search Assistant for Learning Objects",
journal = j-TWEB,
volume = "5",
number = "4",
pages = "21:1--21:??",
month = oct,
year = "2011",
CODEN = "????",
DOI = "https://doi.org/10.1145/2019643.2019648",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:40 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The Web holds a great quantity of material that can be
used to enhance classroom instruction. However, it is
not easy to retrieve this material with the search
engines currently available. This study produced a
specialized search assistant based on Google that
significantly increases the number of instances in
which teachers find the desired learning objects as
compared to using this popular public search engine
directly. Success in finding learning objects by study
participants went from 80\% using Google alone to 96\%
when using our search assistant in one scenario and, in
another scenario, from a 40\% success rate with Google
alone to 66\% with our assistant. This specialized
search assistant implements features such as bilingual
search and term suggestion which were requested by
teacher participants to help improve their searches.
Study participants evaluated the specialized search
assistant and found it significantly easier to use and
more useful than the popular search engine for the
purpose of finding learning objects.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zhu:2012:CLS,
author = "Guangyu Zhu and Gilad Mishne",
title = "{ClickRank}: Learning Session-Context Models to Enrich
{Web} Search Ranking",
journal = j-TWEB,
volume = "6",
number = "1",
pages = "1:1--1:??",
month = mar,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2109205.2109206",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:41 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "User browsing information, particularly
non-search-related activity, reveals important
contextual information on the preferences and intents
of Web users. In this article, we demonstrate the
importance of mining general Web user behavior data to
improve ranking and other Web-search experience, with
an emphasis on analyzing individual user sessions for
creating aggregate models. In this context, we
introduce ClickRank, an efficient, scalable algorithm
for estimating Webpage and Website importance from
general Web user-behavior data. We lay out the
theoretical foundation of ClickRank based on an
intentional surfer model and discuss its properties. We
quantitatively evaluate its effectiveness regarding the
problem of Web-search ranking, showing that it
contributes significantly to retrieval performance as a
novel Web-search feature. We demonstrate that the
results produced by ClickRank for Web-search ranking
are highly competitive with those produced by other
approaches, yet achieved at better scalability and
substantially lower computational costs. Finally, we
discuss novel applications of ClickRank in providing
enriched user Web-search experience, highlighting the
usefulness of our approach for nonranking tasks.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Liu:2012:IWS,
author = "Yiqun Liu and Fei Chen and Weize Kong and Huijia Yu
and Min Zhang and Shaoping Ma and Liyun Ru",
title = "Identifying {Web} Spam with the Wisdom of the Crowds",
journal = j-TWEB,
volume = "6",
number = "1",
pages = "2:1--2:??",
month = mar,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2109205.2109207",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:41 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Combating Web spam has become one of the top
challenges for Web search engines. State-of-the-art
spam-detection techniques are usually designed for
specific, known types of Web spam and are incapable of
dealing with newly appearing spam types efficiently.
With user-behavior analyses from Web access logs, a
spam page-detection algorithm is proposed based on a
learning scheme. The main contributions are the
following. (1) User-visiting patterns of spam pages are
studied, and a number of user-behavior features are
proposed for separating Web spam pages from ordinary
pages. (2) A novel spam-detection framework is proposed
that can detect various kinds of Web spam, including
newly appearing ones, with the help of the
user-behavior analysis. Experiments on large-scale
practical Web access log data show the effectiveness of
the proposed features and the detection framework.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Mesbah:2012:CAB,
author = "Ali Mesbah and Arie van Deursen and Stefan Lenselink",
title = "Crawling {Ajax}-Based {Web} Applications through
Dynamic Analysis of User Interface State Changes",
journal = j-TWEB,
volume = "6",
number = "1",
pages = "3:1--3:??",
month = mar,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2109205.2109208",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:41 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Using JavaScript and dynamic DOM manipulation on the
client side of Web applications is becoming a
widespread approach for achieving rich interactivity
and responsiveness in modern Web applications. At the
same time, such techniques---collectively known as
Ajax---shatter the concept of webpages with unique
URLs, on which traditional Web crawlers are based. This
article describes a novel technique for crawling
Ajax-based applications through automatic dynamic
analysis of user-interface-state changes in Web
browsers. Our algorithm scans the DOM tree, spots
candidate elements that are capable of changing the
state, fires events on those candidate elements, and
incrementally infers a state machine that models the
various navigational paths and states within an Ajax
application. This inferred model can be used in program
comprehension and in analysis and testing of dynamic
Web states, for instance, or for generating a static
version of the application. In this article, we discuss
our sequential and concurrent Ajax crawling algorithms.
We present our open source tool called Crawljax, which
implements the concepts and algorithms discussed in
this article. Additionally, we report a number of
empirical studies in which we apply our approach to a
number of open-source and industrial Web applications
and elaborate on the obtained results.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Lauw:2012:QLO,
author = "Hady W. Lauw and Ee-Peng Lim and Ke Wang",
title = "Quality and Leniency in Online Collaborative Rating
Systems",
journal = j-TWEB,
volume = "6",
number = "1",
pages = "4:1--4:??",
month = mar,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2109205.2109209",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Mar 16 12:37:41 MDT 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The emerging trend of social information processing
has resulted in Web users' increased reliance on
user-generated content contributed by others for
information searching and decision making. Rating
scores, a form of user-generated content contributed by
reviewers in online rating systems, allow users to
leverage others' opinions in the evaluation of objects.
In this article, we focus on the problem of summarizing
the rating scores given to an object into an overall
score that reflects the object's quality. We observe
that the existing approaches for summarizing scores
largely ignores the effect of reviewers exercising
different standards in assigning scores. Instead of
treating all reviewers as equals, our approach models
the leniency of reviewers, which refers to the tendency
of a reviewer to assign higher scores than other
coreviewers. Our approach is underlined by two
insights: (1) The leniency of a reviewer depends not
only on how the reviewer rates objects, but also on how
other reviewers rate those objects and (2) The leniency
of a reviewer and the quality of rated objects are
mutually dependent. We develop the leniency-aware
quality, or LQ model, which solves leniency and quality
simultaneously. We introduce both an exact and a ranked
solution to the model. Experiments on real-life and
synthetic datasets show that LQ is more effective than
comparable approaches. LQ is also shown to perform
consistently better under different parameter
settings.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Ashman:2012:E,
author = "Helen Ashman and Arun Iyengar and Marc Najork",
title = "Editorial",
journal = j-TWEB,
volume = "6",
number = "2",
pages = "5:1--5:??",
month = may,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2180861.2180862",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:48 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{DeCapitaniDiVimercati:2012:ITM,
author = "Sabrina {De Capitani Di Vimercati} and Sara Foresti
and Sushil Jajodia and Stefano Paraboschi and Giuseppe
Psaila and Pierangela Samarati",
title = "Integrating trust management and access control in
data-intensive {Web} applications",
journal = j-TWEB,
volume = "6",
number = "2",
pages = "6:1--6:??",
month = may,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2180861.2180863",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:48 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The widespread diffusion of Web-based services
provided by public and private organizations emphasizes
the need for a flexible solution for protecting the
information accessible through Web applications. A
promising approach is represented by credential-based
access control and trust management. However, although
much research has been done and several proposals
exist, a clear obstacle to the realization of their
benefits in data-intensive Web applications is
represented by the lack of adequate support in the
DBMSs. As a matter of fact, DBMSs are often responsible
for the management of most of the information that is
accessed using a Web browser or a Web service
invocation. In this article, we aim at eliminating this
gap, and present an approach integrating trust
management with the access control of the DBMS. We
propose a trust model with a SQL syntax and illustrate
an algorithm for the efficient verification of a
delegation path for certificates. Our solution nicely
complements current trust management proposals allowing
the efficient realization of the services of an
advanced trust management model within current
relational DBMSs. An important benefit of our approach
lies in its potential for a robust end-to-end design of
security for personal data in Web scenario, where
vulnerabilities of Web applications cannot be used to
violate the protection of the data residing on the
database server. We also illustrate the implementation
of our approach within an open-source DBMS discussing
design choices and performance impact.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Alrifai:2012:HAE,
author = "Mohammad Alrifai and Thomas Risse and Wolfgang Nejdl",
title = "A hybrid approach for efficient {Web} service
composition with end-to-end {QoS} constraints",
journal = j-TWEB,
volume = "6",
number = "2",
pages = "7:1--7:??",
month = may,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2180861.2180864",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:48 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Dynamic selection of Web services at runtime is
important for building flexible and loosely-coupled
service-oriented applications. An abstract description
of the required services is provided at design-time,
and matching service offers are located at runtime.
With the growing number of Web services that provide
the same functionality but differ in quality parameters
(e.g., availability, response time), a decision needs
to be made on which services should be selected such
that the user's end-to-end QoS requirements are
satisfied. Although very efficient, local selection
strategy fails short in handling global QoS
requirements. Solutions based on global optimization,
on the other hand, can handle global constraints, but
their poor performance renders them inappropriate for
applications with dynamic and realtime requirements. In
this article we address this problem and propose a
hybrid solution that combines global optimization with
local selection techniques to benefit from the
advantages of both worlds. The proposed solution
consists of two steps: first, we use mixed integer
programming (MIP) to find the optimal decomposition of
global QoS constraints into local constraints. Second,
we use distributed local selection to find the best Web
services that satisfy these local constraints. The
results of experimental evaluation indicate that our
approach significantly outperforms existing solutions
in terms of computation time while achieving
close-to-optimal results.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Desnoyers:2012:MAM,
author = "Peter Desnoyers and Timothy Wood and Prashant Shenoy
and Rahul Singh and Sangameshwar Patil and Harrick
Vin",
title = "{Modellus}: Automated modeling of complex {Internet}
data center applications",
journal = j-TWEB,
volume = "6",
number = "2",
pages = "8:1--8:??",
month = may,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2180861.2180865",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:48 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The rising complexity of distributed server
applications in Internet data centers has made the
tasks of modeling and analyzing their behavior
increasingly difficult. This article presents Modellus,
a novel system for automated modeling of complex
web-based data center applications using methods from
queuing theory, data mining, and machine learning.
Modellus uses queuing theory and statistical methods to
automatically derive models to predict the resource
usage of an application and the workload it triggers;
these models can be composed to capture multiple
dependencies between interacting applications. Model
accuracy is maintained by fast, distributed testing,
automated relearning of models when they change, and
methods to bound prediction errors in composite models.
We have implemented a prototype of Modellus, deployed
it on a data center testbed, and evaluated its efficacy
for modeling and analysis of several distributed
multitier web applications. Our results show that this
feature-based modeling technique is able to make
predictions across several data center tiers, and
maintain predictive accuracy (typically 95\% or better)
in the face of significant shifts in workload
composition; we also demonstrate practical applications
of the Modellus system to prediction and provisioning
of real-world data center applications.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Aiello:2012:FPH,
author = "Luca Maria Aiello and Alain Barrat and Rossano
Schifanella and Ciro Cattuto and Benjamin Markines and
Filippo Menczer",
title = "Friendship prediction and homophily in social media",
journal = j-TWEB,
volume = "6",
number = "2",
pages = "9:1--9:??",
month = may,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2180861.2180866",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:48 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Social media have attracted considerable attention
because their open-ended nature allows users to create
lightweight semantic scaffolding to organize and share
content. To date, the interplay of the social and
topical components of social media has been only
partially explored. Here, we study the presence of
homophily in three systems that combine tagging social
media with online social networks. We find a
substantial level of topical similarity among users who
are close to each other in the social network. We
introduce a null model that preserves user activity
while removing local correlations, allowing us to
disentangle the actual local similarity between users
from statistical effects due to the assortative mixing
of user activity and centrality in the social network.
This analysis suggests that users with similar
interests are more likely to be friends, and therefore
topical similarity measures among users based solely on
their annotation metadata should be predictive of
social links. We test this hypothesis on several
datasets, confirming that social networks constructed
from topical similarity capture actual friendship
accurately. When combined with topological features,
topical similarity achieves a link prediction accuracy
of about 92\%.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Comai:2012:MDM,
author = "Sara Comai and Davide Mazza",
title = "A model-driven methodology to the content layout
problem in {Web} applications",
journal = j-TWEB,
volume = "6",
number = "3",
pages = "10:1--10:38",
month = sep,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2344416.2344417",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:49 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/texbook3.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This article presents a model-driven approach for the
design of the layout in a complex Web application,
where large amounts of data are accessed. The aim of
this work is to reduce, as much as possible, repetitive
tasks and to factor out common aspects into different
kinds of rules that can be reused across different
applications. In particular, exploiting the conceptual
elements of the typical models used for the design of a
Web application, it defines presentation and layout
rules at different levels of abstraction and
granularity. A procedure for the automatic layout of
the content of a page is proposed and evaluated, and
the layout of advanced Web applications is discussed.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "Automatic contents layout; graphical visualization and
rendering; Web applications design",
}
@Article{Merhav:2012:EIN,
author = "Yuval Merhav and Filipe Mesquita and Denilson Barbosa
and Wai Gen Yee and Ophir Frieder",
title = "Extracting information networks from the blogosphere",
journal = j-TWEB,
volume = "6",
number = "3",
pages = "11:1--11:??",
month = sep,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2344416.2344418",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:49 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We study the problem of automatically extracting
information networks formed by recognizable entities as
well as relations among them from social media sites.
Our approach consists of using state-of-the-art natural
language processing tools to identify entities and
extract sentences that relate such entities, followed
by using text-clustering algorithms to identify the
relations within the information network. We propose a
new term-weighting scheme that significantly improves
on the state-of-the-art in the task of relation
extraction, both when used in conjunction with the
standard tf $ \cdot $ idf scheme and also when used as
a pruning filter. We describe an effective method for
identifying benchmarks for open information extraction
that relies on a curated online database that is
comparable to the hand-crafted evaluation datasets in
the literature. From this benchmark, we derive a much
larger dataset which mimics realistic conditions for
the task of open information extraction. We report on
extensive experiments on both datasets, which not only
shed light on the accuracy levels achieved by
state-of-the-art open information extraction tools, but
also on how to tune such tools for better results.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Miliaraki:2012:FDS,
author = "Iris Miliaraki and Manolis Koubarakis",
title = "{FoXtrot}: Distributed structural and value {XML}
filtering",
journal = j-TWEB,
volume = "6",
number = "3",
pages = "12:1--12:??",
month = sep,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2344416.2344419",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:49 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Publish/subscribe systems have emerged in recent years
as a promising paradigm for offering various popular
notification services. In this context, many XML
filtering systems have been proposed to efficiently
identify XML data that matches user interests expressed
as queries in an XML query language like XPath.
However, in order to offer XML filtering functionality
on an Internet-scale, we need to deploy such a service
in a distributed environment, avoiding bottlenecks that
can deteriorate performance. In this work, we design
and implement FoXtrot, a system for filtering XML data
that combines the strengths of automata for efficient
filtering and distributed hash tables for building a
fully distributed system. Apart from
structural-matching, performed using automata, we also
discuss different methods for evaluating value-based
predicates. We perform an extensive experimental
evaluation of our system, FoXtrot, on a local cluster
and on the PlanetLab network and demonstrate that it
can index millions of user queries, achieving a high
indexing and filtering throughput. At the same time,
FoXtrot exhibits very good load-balancing properties
and improves its performance as we increase the size of
the network.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Dork:2012:NTW,
author = "Marian D{\"o}rk and Carey Williamson and Sheelagh
Carpendale",
title = "Navigating tomorrow's web: From searching and browsing
to visual exploration",
journal = j-TWEB,
volume = "6",
number = "3",
pages = "13:1--13:??",
month = sep,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2344416.2344420",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Nov 6 19:07:49 MST 2012",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We propose a new way of navigating the Web using
interactive information visualizations, and present
encouraging results from a large-scale Web study of a
visual exploration system. While the Web has become an
immense, diverse information space, it has also evolved
into a powerful software platform. We believe that the
established interaction techniques of searching and
browsing do not sufficiently utilize these advances,
since information seekers have to transform their
information needs into specific, text-based search
queries resulting in mostly text-based lists of
resources. In contrast, we foresee a new type of
information seeking that is high-level and more
engaging, by providing the information seeker with
interactive visualizations that give graphical
overviews and enable query formulation. Building on
recent work on faceted navigation, information
visualization, and exploratory search, we conceptualize
this type of information navigation as visual
exploration and evaluate a prototype Web-based system
that implements it. We discuss the results of a
large-scale, mixed-method Web study that provides a
better understanding of the potential benefits of
visual exploration on the Web, and its particular
performance challenges.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cambazoglu:2012:CBQ,
author = "B. Barla Cambazoglu and Ismail Sengor Altingovde and
Rifat Ozcan and {\"O}zg{\"u}r Ulusoy",
title = "Cache-Based Query Processing for Search Engines",
journal = j-TWEB,
volume = "6",
number = "4",
pages = "14:1--14:??",
month = nov,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2382616.2382617",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In practice, a search engine may fail to serve a query
due to various reasons such as hardware/network
failures, excessive query load, lack of matching
documents, or service contract limitations (e.g., the
query rate limits for third-party users of a search
service). In this kind of scenarios, where the backend
search system is unable to generate answers to queries,
approximate answers can be generated by exploiting the
previously computed query results available in the
result cache of the search engine. In this work, we
propose two alternative strategies to implement this
cache-based query processing idea. The first strategy
aggregates the results of similar queries that are
previously cached in order to create synthetic results
for new queries. The second strategy forms an inverted
index over the textual information (i.e., query terms
and result snippets) present in the result cache and
uses this index to answer new queries. Both approaches
achieve reasonable result qualities compared to
processing queries with an inverted index built on the
collection.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Delac:2012:MSS,
author = "Goran Delac and Ivan Budiselic and Ivan Zuzak and Ivan
Skuliber and Tomislav Stefanec",
title = "A Methodology for {SIP} and {SOAP} Integration Using
Application-Specific Protocol Conversion",
journal = j-TWEB,
volume = "6",
number = "4",
pages = "15:1--15:??",
month = nov,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2382616.2382618",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In recent years, the ubiquitous demands for
cross-protocol application access are driving the need
for deeper integration between SIP and SOAP. In this
article we present a novel methodology for integrating
these two protocols. Through an analysis of properties
of SIP and SOAP we show that integration between these
protocols should be based on application-specific
converters. We describe a generic SIP/SOAP gateway that
implements message handling and network and storage
management while relying on application-specific
converters to define session management and message
mapping for a specific set of SIP and SOAP
communication nodes. In order to ease development of
these converters, we introduce an XML-based
domain-specific language for describing
application-specific conversion processes. We show how
conversion processes can be easily specified in the
language using message sequence diagrams of the desired
interaction. We evaluate the presented methodology
through performance analysis of the developed prototype
gateway and high-level comparison with other
solutions.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Jeon:2012:WCP,
author = "Myeongjae Jeon and Youngjae Kim and Jeaho Hwang and
Joonwon Lee and Euiseong Seo",
title = "Workload Characterization and Performance Implications
of Large-Scale Blog Servers",
journal = j-TWEB,
volume = "6",
number = "4",
pages = "16:1--16:??",
month = nov,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2382616.2382619",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "With the ever-increasing popularity of Social Network
Services (SNSs), an understanding of the
characteristics of these services and their effects on
the behavior of their host servers is critical.
However, there has been a lack of research on the
workload characterization of servers running SNS
applications such as blog services. To fill this void,
we empirically characterized real-world Web server logs
collected from one of the largest South Korean blog
hosting sites for 12 consecutive days. The logs consist
of more than 96 million HTTP requests and 4.7TB of
network traffic. Our analysis reveals the following:
(i) The transfer size of nonmultimedia files and blog
articles can be modeled using a truncated Pareto
distribution and a log-normal distribution,
respectively; (ii) user access for blog articles does
not show temporal locality, but is strongly biased
towards those posted with image or audio files. We
additionally discuss the potential performance
improvement through clustering of small files on a blog
page into contiguous disk blocks, which benefits from
the observed file access patterns. Trace-driven
simulations show that, on average, the suggested
approach achieves 60.6\% better system throughput and
reduces the processing time for file access by 30.8\%
compared to the best performance of the Ext4
filesystem.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wilson:2012:BSG,
author = "Christo Wilson and Alessandra Sala and Krishna P. N.
Puttaswamy and Ben Y. Zhao",
title = "Beyond Social Graphs: User Interactions in Online
Social Networks and their Implications",
journal = j-TWEB,
volume = "6",
number = "4",
pages = "17:1--17:??",
month = nov,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2382616.2382620",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Social networks are popular platforms for interaction,
communication, and collaboration between friends.
Researchers have recently proposed an emerging class of
applications that leverage relationships from social
networks to improve security and performance in
applications such as email, Web browsing, and overlay
routing. While these applications often cite social
network connectivity statistics to support their
designs, researchers in psychology and sociology have
repeatedly cast doubt on the practice of inferring
meaningful relationships from social network
connections alone. This leads to the question: ``Are
social links valid indicators of real user interaction?
If not, then how can we quantify these factors to form
a more accurate model for evaluating socially enhanced
applications?'' In this article, we address this
question through a detailed study of user interactions
in the Facebook social network. We propose the use of
``interaction graphs'' to impart meaning to online
social links by quantifying user interactions. We
analyze interaction graphs derived from Facebook user
traces and show that they exhibit significantly lower
levels of the ``small-world'' properties present in
their social graph counterparts. This means that these
graphs have fewer ``supernodes'' with extremely high
degree, and overall graph diameter increases
significantly as a result. To quantify the impact of
our observations, we use both types of graphs to
validate several well-known social-based applications
that rely on graph properties to infuse new
functionality into Internet applications, including
Reliable Email (RE), SybilGuard, and the weighted
cascade influence maximization algorithm. The results
reveal new insights into each of these systems, and
confirm our hypothesis that to obtain realistic and
accurate results, ongoing research on social network
applications studies of social applications should use
real indicators of user interactions in lieu of social
graphs.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Weerkamp:2012:EEC,
author = "Wouter Weerkamp and Krisztian Balog and Maarten de
Rijke",
title = "Exploiting External Collections for Query Expansion",
journal = j-TWEB,
volume = "6",
number = "4",
pages = "18:1--18:??",
month = nov,
year = "2012",
CODEN = "????",
DOI = "https://doi.org/10.1145/2382616.2382621",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "A persisting challenge in the field of information
retrieval is the vocabulary mismatch between a user's
information need and the relevant documents. One way of
addressing this issue is to apply query modeling: to
add terms to the original query and reweigh the terms.
In social media, where documents usually contain
creative and noisy language (e.g., spelling and
grammatical errors), query modeling proves difficult.
To address this, attempts to use external sources for
query modeling have been made and seem to be
successful. In this article we propose a general
generative query expansion model that uses external
document collections for term generation: the External
Expansion Model (EEM). The main rationale behind our
model is our hypothesis that each query requires its
own mixture of external collections for expansion and
that an expansion model should account for this. For
some queries we expect, for example, a news collection
to be most beneficial, while for other queries we could
benefit more by selecting terms from a general
encyclopedia. EEM allows for query-dependent weighing
of the external collections. We put our model to the
test on the task of blog post retrieval and we use four
external collections in our experiments: (i) a news
collection, (ii) a Web collection, (iii) Wikipedia, and
(iv) a blog post collection. Experiments show that EEM
outperforms query expansion on the individual
collections, as well as the Mixture of Relevance Models
that was previously proposed by Diaz and Metzler
[2006]. Extensive analysis of the results shows that
our naive approach to estimating query-dependent
collection importance works reasonably well and that,
when we use ``oracle'' settings, we see the full
potential of our model. We also find that the
query-dependent collection importance has more impact
on retrieval performance than the independent
collection importance (i.e., a collection prior).",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wu:2013:MVC,
author = "Ou Wu and Weiming Hu and Lei Shi",
title = "Measuring the Visual Complexities of {Web} Pages",
journal = j-TWEB,
volume = "7",
number = "1",
pages = "1:1--1:??",
month = mar,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2435215.2435216",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Visual complexities (VisComs) of Web pages
significantly affect user experience, and automatic
evaluation can facilitate a large number of Web-based
applications. The construction of a model for measuring
the VisComs of Web pages requires the extraction of
typical features and learning based on labeled Web
pages. However, as far as the authors are aware, little
headway has been made on measuring VisCom in Web mining
and machine learning. The present article provides a
new approach combining Web mining techniques and
machine learning algorithms for measuring the VisComs
of Web pages. The structure of a Web page is first
analyzed, and the layout is then extracted. Using a Web
page as a semistructured image, three classes of
features are extracted to construct a feature vector.
The feature vector is fed into a learned measuring
function to calculate the VisCom of the page. In the
proposed approach of the present study, the type of the
measuring function and its learning depend on the
quantification strategy for VisCom. Aside from using a
category and a score to represent VisCom as existing
work, this study presents a new strategy utilizing a
distribution to quantify the VisCom of a Web page.
Empirical evaluation suggests the effectiveness of the
proposed approach in terms of both features and
learning algorithms.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Hanson:2013:PWA,
author = "Vicki L. Hanson and John T. Richards",
title = "Progress on {Website} Accessibility?",
journal = j-TWEB,
volume = "7",
number = "1",
pages = "2:1--2:??",
month = mar,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2435215.2435217",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Over 100 top-traffic and government websites from the
United States and United Kingdom were examined for
evidence of changes on accessibility indicators over
the 14-year period from 1999 to 2012, the longest
period studied to date. Automated analyses of WCAG 2.0
Level A Success Criteria found high percentages of
violations overall. Unlike more circumscribed studies,
however, these sites exhibited improvements over the
years on a number of accessibility indicators, with
government sites being less likely than topsites to
have accessibility violations. Examination of the
causes of success and failure suggests that improving
accessibility may be due, in part, to changes in
website technologies and coding practices rather than a
focus on accessibility per se.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Baykan:2013:CST,
author = "Eda Baykan and Monika Henzinger and Ingmar Weber",
title = "A Comprehensive Study of Techniques for {URL}-Based
{Web} Page Language Classification",
journal = j-TWEB,
volume = "7",
number = "1",
pages = "3:1--3:??",
month = mar,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2435215.2435218",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Given only the URL of a Web page, can we identify its
language? In this article we examine this question.
URL-based language classification is useful when the
content of the Web page is not available or downloading
the content is a waste of bandwidth and time. We built
URL-based language classifiers for English, German,
French, Spanish, and Italian by applying a variety of
algorithms and features. As algorithms we used machine
learning algorithms which are widely applied for text
classification and state-of-art algorithms for language
identification of text. As features we used words,
various sized n-grams, and custom-made features (our
novel feature set). We compared our approaches with two
baseline methods, namely classification by country code
top-level domains and classification by IP addresses of
the hosting Web servers. We trained and tested our
classifiers in a 10-fold cross-validation setup on a
dataset obtained from the Open Directory Project and
from querying a commercial search engine. We obtained
the lowest F1-measure for English (94) and the highest
F1-measure for German (98) with the best performing
classifiers. We also evaluated the performance of our
methods: (i) on a set of Web pages written in Adobe
Flash and (ii) as part of a language-focused crawler.
In the first case, the content of the Web page is hard
to extract and in the second page downloading pages of
the ``wrong'' language constitutes a waste of
bandwidth. In both settings the best classifiers have a
high accuracy with an F1-measure between 95 (for
English) and 98 (for Italian) for the Adobe Flash pages
and a precision between 90 (for Italian) and 97 (for
French) for the language-focused crawler.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Marriott:2013:HAT,
author = "Kim Marriott and Peter Moulder and Nathan Hurst",
title = "{HTML} Automatic Table Layout",
journal = j-TWEB,
volume = "7",
number = "1",
pages = "4:1--4:??",
month = mar,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2435215.2435219",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sun May 5 09:27:25 MDT 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Automatic layout of tables is required in online
applications because of the need to tailor the layout
to the viewport width, choice of font, and dynamic
content. However, if the table contains text,
minimizing the height of the table for a fixed maximum
width is NP-hard. Thus, more efficient heuristic
algorithms are required. We evaluate the HTML table
layout recommendation and find that while it generally
produces quite compact layout it is brittle and can
lead to quite uncompact layout. We present an alternate
heuristic algorithm. It uses a greedy strategy that
starts from the widest reasonable layout and repeatedly
chooses to narrow the column for which narrowing leads
to the least increase in table height. The algorithm is
simple, fast enough to be used in online applications,
and gives significantly more compact layout than is
obtained with HTML's recommended table layout
algorithm.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Anisetti:2013:TBS,
author = "Marco Anisetti and Claudio A. Ardagna and Ernesto
Damiani and Francesco Saonara",
title = "A test-based security certification scheme for {Web}
services",
journal = j-TWEB,
volume = "7",
number = "2",
pages = "5:1--5:??",
month = may,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2460383.2460384",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:18 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The Service-Oriented Architecture (SOA) paradigm is
giving rise to a new generation of applications built
by dynamically composing loosely coupled autonomous
services. Clients (i.e., software agents acting on
behalf of human users or service providers)
implementing such complex applications typically search
and integrate services on the basis of their functional
requirements and of their trust in the service
suppliers. A major issue in this scenario relates to
the definition of an assurance technique allowing
clients to select services on the basis of their
nonfunctional requirements and increasing their
confidence that the selected services will satisfy such
requirements. In this article, we first present an
assurance solution that focuses on security and
supports a test-based security certification scheme for
Web services. The certification scheme is driven by the
security properties to be certified and relies upon a
formal definition of the service model. The evidence
supporting a certified property is computed using a
model-based testing approach that, starting from the
service model, automatically generates the test cases
to be used in the service certification. We also define
a set of indexes and metrics that evaluate the
assurance level and the quality of the certification
process. Finally, we present our evaluation toolkit and
experimental results obtained applying our
certification solution to a financial service
implementing the Interactive Financial eXchange (IFX)
standard.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Victor:2013:ETB,
author = "Patricia Victor and Nele Verbiest and Chris Cornelis
and Martine {De Cock}",
title = "Enhancing the trust-based recommendation process with
explicit distrust",
journal = j-TWEB,
volume = "7",
number = "2",
pages = "6:1--6:??",
month = may,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2460383.2460385",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:18 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "When a Web application with a built-in recommender
offers a social networking component which enables its
users to form a trust network, it can generate more
personalized recommendations by combining user ratings
with information from the trust network. These are the
so-called trust-enhanced recommendation systems. While
research on the incorporation of trust for
recommendations is thriving, the potential of
explicitly stated distrust remains almost unexplored.
In this article, we introduce a distrust-enhanced
recommendation algorithm which has its roots in
Golbeck's trust-based weighted mean. Through
experiments on a set of reviews from Epinions.com, we
show that our new algorithm outperforms its standard
trust-only counterpart with respect to accuracy,
thereby demonstrating the positive effect that explicit
distrust can have on trust-based recommendations.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Yue:2013:MSI,
author = "Chuan Yue and Haining Wang",
title = "A measurement study of insecure {JavaScript} practices
on the {Web}",
journal = j-TWEB,
volume = "7",
number = "2",
pages = "7:1--7:??",
month = may,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2460383.2460386",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:18 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/java2010.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "JavaScript is an interpreted programming language most
often used for enhancing webpage interactivity and
functionality. It has powerful capabilities to interact
with webpage documents and browser windows, however, it
has also opened the door for many browser-based
security attacks. Insecure engineering practices of
using JavaScript may not directly lead to security
breaches, but they can create new attack vectors and
greatly increase the risks of browser-based attacks. In
this article, we present the first measurement study on
insecure practices of using JavaScript on the Web. Our
focus is on the insecure practices of JavaScript
inclusion and dynamic generation, and we examine their
severity and nature on 6,805 unique websites. Our
measurement results reveal that insecure JavaScript
practices are common at various websites: (1) at least
66.4\% of the measured websites manifest the insecure
practices of including JavaScript files from external
domains into the top-level documents of their webpages;
(2) over 44.4\% of the measured websites use the
dangerous eval() function to dynamically generate and
execute JavaScript code on their webpages; and (3) in
JavaScript dynamic generation, using the
document.write() method and the innerHTML property is
much more popular than using the relatively secure
technique of creating script elements via DOM methods.
Our analysis indicates that safe alternatives to these
insecure practices exist in common cases and ought to
be adopted by website developers and administrators for
reducing potential security risks.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Su:2013:UQI,
author = "Weifeng Su and Hejun Wu and Yafei Li and Jing Zhao and
Frederick H. Lochovsky and Hongmin Cai and Tianqiang
Huang",
title = "Understanding query interfaces by statistical
parsing",
journal = j-TWEB,
volume = "7",
number = "2",
pages = "8:1--8:??",
month = may,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2460383.2460387",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:18 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Users submit queries to an online database via its
query interface. Query interface parsing, which is
important for many applications, understands the query
capabilities of a query interface. Since most query
interfaces are organized hierarchically, we present a
novel query interface parsing method, StatParser
(Statistical Parser), to automatically extract the
hierarchical query capabilities of query interfaces.
StatParser automatically learns from a set of parsed
query interfaces and parses new query interfaces.
StatParser starts from a small grammar and enhances the
grammar with a set of probabilities learned from parsed
query interfaces under the maximum-entropy principle.
Given a new query interface, the probability-enhanced
grammar identifies the parse tree with the largest
global probability to be the query capabilities of the
query interface. Experimental results show that
StatParser very accurately extracts the query
capabilities and can effectively overcome the problems
of existing query interface parsers.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Diaz:2013:LEU,
author = "Oscar D{\'\i}az and Crist{\'o}bal Arellano and Maider
Azanza",
title = "A language for end-user {Web} augmentation: Caring for
producers and consumers alike",
journal = j-TWEB,
volume = "7",
number = "2",
pages = "9:1--9:??",
month = may,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2460383.2460388",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:18 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/java2010.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Web augmentation is to the Web what augmented reality
is to the physical world: layering relevant
content/layout/navigation over the existing Web to
customize the user experience. This is achieved through
JavaScript (JS) using browser weavers (e.g.,
Greasemonkey). To date, over 43 million of downloads of
Greasemonkey scripts ground the vitality of this
movement. However, Web augmentation is hindered by
being programming intensive and prone to malware. This
prevents end-users from participating as both producers
and consumers of scripts: producers need to know JS,
consumers need to trust JS. This article aims at
promoting end-user participation in both roles. The
vision is for end-users to prosume (the act of
simultaneously caring for producing and consuming)
scripts as easily as they currently prosume their
pictures or videos. Encouraging production requires
more ``natural'' and abstract constructs. Promoting
consumption calls for augmentation scripts to be easier
to understand, share, and trust upon. To this end, we
explore the use of Domain-Specific Languages (DSLs) by
introducing Sticklet. Sticklet is an internal DSL on
JS, where JS generality is reduced for the sake of
learnability and reliability. Specifically, Web
augmentation is conceived as fixing in existing web
sites (i.e., the wall ) HTML fragments extracted from
either other sites or Web services (i.e., the stickers
). Sticklet targets hobby programmers as producers, and
computer literates as consumers. From a producer
perspective, benefits are threefold. As a restricted
grammar on top of JS, Sticklet expressions are domain
oriented and more declarative than their JS
counterparts, hence speeding up development. As
syntactically correct JS expressions, Sticklet scripts
can be installed as traditional scripts and hence,
programmers can continue using existing JS tools. As
declarative expressions, they are easier to maintain,
and amenable for optimization. From a consumer
perspective, domain specificity brings
understandability (due to declarativeness), reliability
(due to built-in security), and ``consumability''
(i.e., installation/enactment/sharing of Sticklet
expressions are tuned to the shortage of time and
skills of the target audience). Preliminary evaluations
indicate that 77\% of the subjects were able to develop
new Sticklet scripts in less than thirty minutes while
84\% were able to consume these scripts in less than
ten minutes. Sticklet is available to download as a
Mozilla add-on.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Kaldeli:2013:CWS,
author = "Eirini Kaldeli and Ehsan Ullah Warriach and Alexander
Lazovik and Marco Aiello",
title = "Coordinating the web of services for a smart home",
journal = j-TWEB,
volume = "7",
number = "2",
pages = "10:1--10:??",
month = may,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2460383.2460389",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:18 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Domotics, concerned with the realization of
intelligent home environments, is a novel field which
can highly benefit from solutions inspired by
service-oriented principles to enhance the convenience
and security of modern home residents. In this work, we
present an architecture for a smart home, starting from
the lower device interconnectivity level up to the
higher application layers that undertake the load of
complex functionalities and provide a number of
services to end-users. We claim that in order for smart
homes to exhibit a genuinely intelligent behavior, the
ability to compute compositions of individual devices
automatically and dynamically is paramount. To this
end, we incorporate into the architecture a composition
component that employs artificial intelligence
domain-independent planning to generate compositions at
runtime, in a constantly evolving environment. We have
implemented a fully working prototype that realizes
such an architecture, and have evaluated it both in
terms of performance as well as from the end-user point
of view. The results of the evaluation show that the
service-oriented architectural design and the support
for dynamic compositions is quite efficient from the
technical point of view, and that the system succeeds
in satisfying the expectations and objectives of the
users.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Balakrishnan:2013:ART,
author = "Raju Balakrishnan and Subbarao Kambhampati and
Manishkumar Jha",
title = "Assessing relevance and trust of the deep web sources
and results based on inter-source agreement",
journal = j-TWEB,
volume = "7",
number = "2",
pages = "11:1--11:??",
month = may,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2460383.2460390",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:18 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Deep web search engines face the formidable challenge
of retrieving high-quality results from the vast
collection of searchable databases. Deep web search is
a two-step process of selecting the high-quality
sources and ranking the results from the selected
sources. Though there are existing methods for both the
steps, they assess the relevance of the sources and the
results using the query-result similarity. When applied
to the deep web these methods have two deficiencies.
First is that they are agnostic to the correctness
(trustworthiness) of the results. Second, the
query-based relevance does not consider the importance
of the results and sources. These two considerations
are essential for the deep web and open collections in
general. Since a number of deep web sources provide
answers to any query, we conjuncture that the
agreements between these answers are helpful in
assessing the importance and the trustworthiness of the
sources and the results. For assessing source quality,
we compute the agreement between the sources as the
agreement of the answers returned. While computing the
agreement, we also measure and compensate for the
possible collusion between the sources. This adjusted
agreement is modeled as a graph with sources at the
vertices. On this agreement graph, a quality score of a
source, that we call SourceRank, is calculated as the
stationary visit probability of a random walk. For
ranking results, we analyze the second-order agreement
between the results. Further extending SourceRank to
multidomain search, we propose a source ranking
sensitive to the query domains. Multiple
domain-specific rankings of a source are computed, and
these ranks are combined for the final ranking. We
perform extensive evaluations on online and hundreds of
Google Base sources spanning across domains. The
proposed result and source rankings are implemented in
the deep web search engine Factal. We demonstrate that
the agreement analysis tracks source corruption.
Further, our relevance evaluations show that our
methods improve precision significantly over Google
Base and the other baseline methods. The result ranking
and the domain-specific source ranking are evaluated
separately.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Nguyen:2013:FWT,
author = "Cam-Tu Nguyen and Natsuda Kaothanthong and Takeshi
Tokuyama and Xuan-Hieu Phan",
title = "A feature-word-topic model for image annotation and
retrieval",
journal = j-TWEB,
volume = "7",
number = "3",
pages = "12:1--12:??",
month = sep,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2516633.2516634",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:20 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Image annotation is a process of finding appropriate
semantic labels for images in order to obtain a more
convenient way for indexing and searching images on the
Web. This article proposes a novel method for image
annotation based on combining feature-word
distributions, which map from visual space to word
space, and word-topic distributions, which form a
structure to capture label relationships for
annotation. We refer to this type of model as
Feature-Word-Topic models. The introduction of topics
allows us to efficiently take word associations, such
as {ocean, fish, coral} or {desert, sand, cactus}, into
account for image annotation. Unlike previous
topic-based methods, we do not consider topics as joint
distributions of words and visual features, but as
distributions of words only. Feature-word distributions
are utilized to define weights in computation of topic
distributions for annotation. By doing so, topic models
in text mining can be applied directly in our method.
Our Feature-word-topic model, which exploits Gaussian
Mixtures for feature-word distributions, and
probabilistic Latent Semantic Analysis (pLSA) for
word-topic distributions, shows that our method is able
to obtain promising results in image annotation and
retrieval.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Vargiu:2013:ICA,
author = "Eloisa Vargiu and Alessandro Giuliani and Giuliano
Armano",
title = "Improving contextual advertising by adopting
collaborative filtering",
journal = j-TWEB,
volume = "7",
number = "3",
pages = "13:1--13:??",
month = sep,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2516633.2516635",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:20 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Contextual advertising can be viewed as an information
filtering task aimed at selecting suitable ads to be
suggested to the final ``user'', that is, the Web page
in hand. Starting from this insight, in this article we
propose a novel system, which adopts a collaborative
filtering approach to perform contextual advertising.
In particular, given a Web page, the system relies on
collaborative filtering to classify the page content
and to suggest suitable ads accordingly. Useful
information is extracted from ``inlinks'', that is,
similar pages that link to the Web page in hand. In so
doing, collaborative filtering is used in a
content-based setting, giving rise to a hybrid
contextual advertising system. After being implemented,
the system has been experimented with about 15000 Web
pages extracted from the Open Directory Project.
Comparative experiments with a content-based system
have been performed. The corresponding results
highlight that the proposed system performs better. A
suitable case study is also provided to enable the
reader to better understand how the system works and
its effectiveness.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Conti:2013:VPS,
author = "Mauro Conti and Arbnor Hasani and Bruno Crispo",
title = "Virtual private social networks and a {Facebook}
implementation",
journal = j-TWEB,
volume = "7",
number = "3",
pages = "14:1--14:??",
month = sep,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2516633.2516636",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:20 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The popularity of Social Networking Sites (SNS) is
growing rapidly, with the largest sites serving
hundreds of millions of users and their private
information. The privacy settings of these SNSs do not
allow the user to avoid sharing some information (e.g.,
name and profile picture) with all the other users.
Also, no matter the privacy settings, this information
is always shared with the SNS (that could sell this
information or be hacked). To mitigate these threats,
we recently introduced the concept of Virtual Private
Social Networks (VPSNs). In this work we propose the
first complete architecture and implementation of VPSNs
for Facebook. In particular, we address an important
problem left unexplored in our previous research-that
is the automatic propagation of updated profiles to all
the members of the same VPSN. Furthermore, we made an
in-depth study on performance and implemented several
optimization to reduce the impact of VPSN on user
experience. The proposed solution is lightweight,
completely distributed, does not depend on the
collaboration from Facebook, does not have a central
point of failure, it offers (with some limitations) the
same functionality as Facebook, and apart from some
simple settings, the solution is almost transparent to
the user. Thorough experiments, with an extended set of
parameters, we have confirmed the feasibility of the
proposal and have shown a very limited time-overhead
experienced by the user while browsing Facebook
pages.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cambazoglu:2013:TBI,
author = "B. Barla Cambazoglu and Enver Kayaaslan and Simon
Jonassen and Cevdet Aykanat",
title = "A term-based inverted index partitioning model for
efficient distributed query processing",
journal = j-TWEB,
volume = "7",
number = "3",
pages = "15:1--15:??",
month = sep,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2516633.2516637",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:20 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In a shared-nothing, distributed text retrieval
system, queries are processed over an inverted index
that is partitioned among a number of index servers. In
practice, the index is either document-based or
term-based partitioned. This choice is made depending
on the properties of the underlying hardware
infrastructure, query traffic distribution, and some
performance and availability constraints. In query
processing on retrieval systems that adopt a term-based
index partitioning strategy, the high communication
overhead due to the transfer of large amounts of data
from the index servers forms a major performance
bottleneck, deteriorating the scalability of the entire
distributed retrieval system. In this work, to
alleviate this problem, we propose a novel inverted
index partitioning model that relies on hypergraph
partitioning. In the proposed model, concurrently
accessed index entries are assigned to the same index
servers, based on the inverted index access patterns
extracted from the past query logs. The model aims to
minimize the communication overhead that will be
incurred by future queries while maintaining the
computational load balance among the index servers. We
evaluate the performance of the proposed model through
extensive experiments using a real-life text collection
and a search query sample. Our results show that
considerable performance gains can be achieved relative
to the term-based index partitioning strategies
previously proposed in literature. In most cases,
however, the performance remains inferior to that
attained by document-based partitioning.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Weninger:2013:PPF,
author = "Tim Weninger and Thomas J. Johnston and Jiawei Han",
title = "The parallel path framework for entity discovery on
the web",
journal = j-TWEB,
volume = "7",
number = "3",
pages = "16:1--16:??",
month = sep,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2516633.2516638",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:20 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "It has been a dream of the database and Web
communities to reconcile the unstructured nature of the
World Wide Web with the neat, structured schemas of the
database paradigm. Even though databases are currently
used to generate Web content in some sites, the schemas
of these databases are rarely consistent across a
domain. This makes the comparison and aggregation of
information from different domains difficult. We aim to
make an important step towards resolving this disparity
by using the structural and relational information on
the Web to (1) extract Web lists, (2) find
entity-pages, (3) map entity-pages to a database, and
(4) extract attributes of the entities. Specifically,
given a Web site and an entity-page (e.g., university
department and faculty member home page) we seek to
find all of the entity-pages of the same type (e.g.,
all faculty members in the department), as well as
attributes of the specific entities (e.g., their phone
numbers, email addresses, office numbers). To do this,
we propose a Web structure mining method which grows
parallel paths through the Web graph and DOM trees and
propagates relevant attribute information forward. We
show that by utilizing these parallel paths we can
efficiently discover entity-pages and attributes.
Finally, we demonstrate the accuracy of our method with
a large case study.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Liu:2013:SCB,
author = "Liwei Liu and Freddy Lecue and Nikolay Mehandjiev",
title = "Semantic content-based recommendation of software
services using context",
journal = j-TWEB,
volume = "7",
number = "3",
pages = "17:1--17:??",
month = sep,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2516633.2516639",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:20 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The current proliferation of software services means
users should be supported when selecting one service
out of the many which meet their needs. Recommender
Systems provide such support for selecting products and
conventional services, yet their direct application to
software services is not straightforward, because of
the current scarcity of available user feedback, and
the need to fine-tune software services to the context
of intended use. In this article, we address these
issues by proposing a semantic content-based
recommendation approach that analyzes the context of
intended service use to provide effective
recommendations in conditions of scarce user feedback.
The article ends with two experiments based on a
realistic set of semantic services. The first
experiment demonstrates how the proposed semantic
content-based approach can produce effective
recommendations using semantic reasoning over service
specifications by comparing it with three other
approaches. The second experiment demonstrates the
effectiveness of the proposed context analysis
mechanism by comparing the performance of both
context-aware and plain versions of our semantic
content-based approach, benchmarked against
user-performed selection informed by context.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Jiang:2013:ULI,
author = "Jing Jiang and Christo Wilson and Xiao Wang and
Wenpeng Sha and Peng Huang and Yafei Dai and Ben Y.
Zhao",
title = "Understanding latent interactions in online social
networks",
journal = j-TWEB,
volume = "7",
number = "4",
pages = "18:1--18:??",
month = oct,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2517040",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:21 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Popular online social networks (OSNs) like Facebook
and Twitter are changing the way users communicate and
interact with the Internet. A deep understanding of
user interactions in OSNs can provide important
insights into questions of human social behavior and
into the design of social platforms and applications.
However, recent studies have shown that a majority of
user interactions on OSNs are latent interactions, that
is, passive actions, such as profile browsing, that
cannot be observed by traditional measurement
techniques. In this article, we seek a deeper
understanding of both active and latent user
interactions in OSNs. For quantifiable data on latent
user interactions, we perform a detailed measurement
study on Renren, the largest OSN in China with more
than 220 million users to date. All friendship links in
Renren are public, allowing us to exhaustively crawl a
connected graph component of 42 million users and 1.66
billion social links in 2009. Renren also keeps
detailed, publicly viewable visitor logs for each user
profile. We capture detailed histories of profile
visits over a period of 90 days for users in the Peking
University Renren network and use statistics of profile
visits to study issues of user profile popularity,
reciprocity of profile visits, and the impact of
content updates on user popularity. We find that latent
interactions are much more prevalent and frequent than
active events, are nonreciprocal in nature, and that
profile popularity is correlated with page views of
content rather than with quantity of content updates.
Finally, we construct latent interaction graphs as
models of user browsing behavior and compare their
structural properties, evolution, community structure,
and mixing times against those of both active
interaction graphs and social graphs.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Quarteroni:2013:BKA,
author = "Silvia Quarteroni and Marco Brambilla and Stefano
Ceri",
title = "A bottom-up, knowledge-aware approach to integrating
and querying {Web} data services",
journal = j-TWEB,
volume = "7",
number = "4",
pages = "19:1--19:??",
month = oct,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2493536",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:21 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "As a wealth of data services is becoming available on
the Web, building and querying Web applications that
effectively integrate their content is increasingly
important. However, schema integration and ontology
matching with the aim of registering data services
often requires a knowledge-intensive, tedious, and
error-prone manual process. We tackle this issue by
presenting a bottom-up, semi-automatic service
registration process that refers to an external
knowledge base and uses simple text processing
techniques in order to minimize and possibly avoid the
contribution of domain experts in the annotation of
data services. The first by-product of this process is
a representation of the domain of data services as an
entity-relationship diagram, whose entities are named
after concepts of the external knowledge base matching
service terminology rather than being manually created
to accommodate an application-specific ontology.
Second, a three-layer annotation of service semantics
(service interfaces, access patterns, service marts)
describing how services ``play'' with such domain
elements is also automatically constructed at
registration time. When evaluated against heterogeneous
existing data services and with a synthetic service
dataset constructed using Google Fusion Tables, the
approach yields good results in terms of data
representation accuracy. We subsequently demonstrate
that natural language processing methods can be used to
decompose and match simple queries to the data services
represented in three layers according to the preceding
methodology with satisfactory results. We show how
semantic annotations are used at query time to convert
the user's request into an executable logical query.
Globally, our findings show that the proposed
registration method is effective in creating a uniform
semantic representation of data services, suitable for
building Web applications and answering search
queries.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Leiva:2013:WBB,
author = "Luis A. Leiva and Roberto Viv{\'o}",
title = "{Web} browsing behavior analysis and interactive
hypervideo",
journal = j-TWEB,
volume = "7",
number = "4",
pages = "20:1--20:??",
month = oct,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2529995.2529996",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:21 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Processing data on any sort of user interaction is
well known to be cumbersome and mostly time consuming.
In order to assist researchers in easily inspecting
fine-grained browsing data, current tools usually
display user interactions as mouse cursor tracks, a
video-like visualization scheme. However, to date,
traditional online video inspection has not explored
the full capabilities of hypermedia and interactive
techniques. In response to this need, we have developed
SMT2$\epsilon$, a Web-based tracking system for
analyzing browsing behavior using feature-rich
hypervideo visualizations. We compare our system to
related work in academia and the industry, showing that
ours features unprecedented visualization capabilities.
We also show that SMT2$\epsilon$ efficiently captures
browsing data and is perceived by users to be both
helpful and usable. A series of prediction experiments
illustrate that raw cursor data are accessible and can
be easily handled, providing evidence that the data can
be used to construct and verify research hypotheses.
Considering its limitations, it is our hope that
SMT2$\epsilon$ will assist researchers, usability
practitioners, and other professionals interested in
understanding how users browse the Web.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bing:2013:RDS,
author = "Lidong Bing and Wai Lam and Tak-Lam Wong",
title = "Robust detection of semi-structured web records using
a {DOM} structure-knowledge-driven model",
journal = j-TWEB,
volume = "7",
number = "4",
pages = "21:1--21:??",
month = oct,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2508434",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:21 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Web data record extraction aims at extracting a set of
similar object records from a single webpage. These
records have similar attributes or fields and are
presented with a regular format in a coherent region of
the page. To tackle this problem, most existing works
analyze the DOM tree of an input page. One major
limitation of these methods is that the lack of a
global view in detecting data records from an input
page results in a myopic decision. Their brute-force
searching manner in detecting various types of records
degrades the flexibility and robustness. We propose a
Structure-Knowledge-Oriented Global Analysis (Skoga)
framework which can perform robust detection of
different-kinds of data records and record regions. The
major component of the Skoga framework is a DOM
structure-knowledge-driven detection model which can
conduct a global analysis on the DOM structure to
achieve effective detection. The DOM structure
knowledge consists of background knowledge as well as
statistical knowledge capturing different
characteristics of data records and record regions, as
exhibited in the DOM structure. The background
knowledge encodes the semantics of labels indicating
general constituents of data records and regions. The
statistical knowledge is represented by some carefully
designed features that capture different
characteristics of a single node or a node group in the
DOM. The feature weights are determined using a
development dataset via a parameter estimation
algorithm based on a structured output support vector
machine. An optimization method based on the
divide-and-conquer principle is developed making use of
the DOM structure knowledge to quantitatively infer and
recognize appropriate records and regions for a page.
Extensive experiments have been conducted on four
datasets. The experimental results demonstrate that our
framework achieves higher accuracy compared with
state-of-the-art methods.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Liao:2013:VAC,
author = "Zhen Liao and Daxin Jiang and Jian Pei and Yalou Huang
and Enhong Chen and Huanhuan Cao and Hang Li",
title = "A {vlHMM} approach to context-aware search",
journal = j-TWEB,
volume = "7",
number = "4",
pages = "22:1--22:??",
month = oct,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2490255",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:21 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Capturing the context of a user's query from the
previous queries and clicks in the same session leads
to a better understanding of the user's information
need. A context-aware approach to document reranking,
URL recommendation, and query suggestion may
substantially improve users' search experience. In this
article, we propose a general approach to context-aware
search by learning a variable length hidden Markov
model ( vlHMM ) from search sessions extracted from log
data. While the mathematical model is powerful, the
huge amounts of log data present great challenges. We
develop several distributed learning techniques to
learn a very large vlHMM under the map-reduce
framework. Moreover, we construct feature vectors for
each state of the vlHMM model to handle users' novel
queries not covered by the training data. We test our
approach on a raw dataset consisting of 1.9 billion
queries, 2.9 billion clicks, and 1.2 billion search
sessions before filtering, and evaluate the
effectiveness of the vlHMM learned from the real data
on three search applications: document reranking, query
suggestion, and URL recommendation. The experiment
results validate the effectiveness of vlHMM in the
applications of document reranking, URL recommendation,
and query suggestion.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "22",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{White:2013:CBD,
author = "Ryen W. White and Eric Horvitz",
title = "Captions and biases in diagnostic search",
journal = j-TWEB,
volume = "7",
number = "4",
pages = "23:1--23:??",
month = oct,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2486040",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:21 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "People frequently turn to the Web with the goal of
diagnosing medical symptoms. Studies have shown that
diagnostic search can often lead to anxiety about the
possibility that symptoms are explained by the presence
of rare, serious medical disorders, rather than far
more common benign syndromes. We study the influence of
the appearance of potentially-alarming content, such as
severe illnesses or serious treatment options
associated with the queried for symptoms, in captions
comprising titles, snippets, and URLs. We explore
whether users are drawn to results with
potentially-alarming caption content, and if so, the
implications of such attraction for the design of
search engines. We specifically study the influence of
the content of search result captions shown in response
to symptom searches on search-result click-through
behavior. We show that users are significantly more
likely to examine and click on captions containing
potentially-alarming medical terminology such as
``heart attack'' or ``medical emergency'' independent
of result rank position and well-known positional
biases in users' search examination behaviors. The
findings provide insights about the possible effects of
displaying implicit correlates of searchers' goals in
search-result captions, such as unexpressed concerns
and fears. As an illustration of the potential utility
of these results, we developed and evaluated an
enhanced click prediction model that incorporates
potentially-alarming caption features and show that it
significantly outperforms models that ignore caption
content. Beyond providing additional understanding of
the effects of Web content on medical concerns, the
methods and findings have implications for search
engine design. As part of our discussion on the
implications of this research, we propose procedures
for generating more representative captions that may be
less likely to cause alarm, as well as methods for
learning to more appropriately rank search results from
logged search behavior, for examples, by also
considering the presence of potentially-alarming
content in the captions that motivate observed clicks
and down-weighting clicks seemingly driven by
searchers' health anxieties.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "23",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Lee:2013:SCA,
author = "Jung-Hyun Lee and Jongwoo Ha and Jin-Yong Jung and
Sangkeun Lee",
title = "Semantic contextual advertising based on the open
directory project",
journal = j-TWEB,
volume = "7",
number = "4",
pages = "24:1--24:??",
month = oct,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2529995.2529997",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:21 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Contextual advertising seeks to place relevant textual
ads within the content of generic webpages. In this
article, we explore a novel semantic approach to
contextual advertising. This consists of three tasks:
(1) building a well-organized hierarchical taxonomy of
topics, (2) developing a robust classifier for
effectively finding the topics of pages and ads, and
(3) ranking ads based on the topical relevance to
pages. First, we heuristically build our own taxonomy
of topics from the Open Directory Project (ODP).
Second, we investigate how to increase classification
accuracy by taking the unique characteristics of the
ODP into account. Last, we measure the topical
relevance of ads by applying a link analysis technique
to the similarity graph carefully derived from our
taxonomy. Experiments show that our classification
method improves the performance of Ma- F$_1$ by as much
as 25.7\% over the baseline classifier. In addition,
our ranking method enhances the relevance of ads
substantially, up to 10\% in terms of precision at k,
compared to a representative strategy.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "24",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Huang:2013:UEQ,
author = "Xiaodi Huang",
title = "{UsageQoS}: Estimating the {QoS} of {Web} Services
through Online User Communities",
journal = j-TWEB,
volume = "8",
number = "1",
pages = "1:1--1:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2532635",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:23 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Services are an indispensable component in cloud
computing. Web services are particularly important. As
an increasing number of Web services provides
equivalent functions, one common issue faced by users
is the selection of the most appropriate one based on
quality. This article presents a conceptual framework
that characterizes the quality of Web services, an
algorithm that quantifies them, and a system
architecture that ranks Web services by using the
proposed algorithm. In particular, the algorithm,
called UsageQoS that computes the scores of quality of
service (QoS) of Web services within a community, makes
use of the usage frequencies of Web services. The
frequencies are defined as the numbers of times invoked
by other services in a given time period. The UsageQoS
algorithm is able to optionally take user ratings as
its initial input. The proposed approach has been
validated by extensively experimenting on several
datasets, including two real datasets. The results of
the experiments have demonstrated that our approach is
capable of estimating QoS parameters of Web services,
regardless of whether user ratings are available or
not.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Weber:2013:FBW,
author = "Ingo Weber and Hye-Young Paik and Boualem Benatallah",
title = "Form-Based {Web} Service Composition for Domain
Experts",
journal = j-TWEB,
volume = "8",
number = "1",
pages = "2:1--2:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2542168",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:23 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In many cases, it is not cost effective to automate
business processes which affect a small number of
people and/or change frequently. We present a novel
approach for enabling domain experts to model and
deploy such processes from their respective domain as
Web service compositions. The approach builds on
user-editable service, naming and representing Web
services as forms. On this basis, the approach provides
a visual composition language with a targeted
restriction of control-flow expressivity, process
simulation, automated process verification mechanisms,
and code generation for executing orchestrations. A
Web-based service composition prototype implements this
approach, including a WS-BPEL code generator. A small
lab user study with 14 participants showed promising
results for the usability of the system, even for
nontechnical domain experts.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Ozcan:2013:SCH,
author = "Rifat Ozcan and Ismail Sengor Altingovde and B. Barla
Cambazoglu and {\"O}zg{\"u}r Ulusoy",
title = "Second Chance: a Hybrid Approach for Dynamic Result
Caching and Prefetching in Search Engines",
journal = j-TWEB,
volume = "8",
number = "1",
pages = "3:1--3:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2536777",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:23 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Web search engines are known to cache the results of
previously issued queries. The stored results typically
contain the document summaries and some data that is
used to construct the final search result page returned
to the user. An alternative strategy is to store in the
cache only the result document IDs, which take much
less space, allowing results of more queries to be
cached. These two strategies lead to an interesting
trade-off between the hit rate and the average query
response latency. In this work, in order to exploit
this trade-off, we propose a hybrid result caching
strategy where a dynamic result cache is split into two
sections: an HTML cache and a docID cache. Moreover,
using a realistic cost model, we evaluate the
performance of different result prefetching strategies
for the proposed hybrid cache and the baseline
HTML-only cache. Finally, we propose a machine learning
approach to predict singleton queries, which occur only
once in the query stream. We show that when the
proposed hybrid result caching strategy is coupled with
the singleton query predictor, the hit rate is further
improved.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Sherkat:2013:ETS,
author = "Reza Sherkat and Jing Li and Nikos Mamoulis",
title = "Efficient Time-Stamped Event Sequence Anonymization",
journal = j-TWEB,
volume = "8",
number = "1",
pages = "4:1--4:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2532643",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:23 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "With the rapid growth of applications which generate
timestamped sequences (click streams, GPS trajectories,
RFID sequences), sequence anonymization has become an
important problem, in that should such data be
published or shared. Existing trajectory anonymization
techniques disregard the importance of time or the
sensitivity of events. This article is the first, to
our knowledge, thorough study on time-stamped event
sequence anonymization. We propose a novel and tunable
generalization framework tailored to event sequences.
We generalize time stamps using time intervals and
events using a taxonomy which models the domain
semantics. We consider two scenarios: (i) sharing the
data with a single receiver (the SSR setting), where
the receiver's background knowledge is confined to a
set of time stamps and time generalization suffices,
and (ii) sharing the data with colluding receivers (the
SCR setting), where time generalization should be
combined with event generalization. For both cases, we
propose appropriate anonymization methods that prevent
both user identification and event prediction. To
achieve computational efficiency and scalability, we
propose optimization techniques for both cases using a
utility-based index, compact summaries, fast to compute
bounds for utility, and a novel taxonomy-aware distance
function. Extensive experiments confirm the
effectiveness of our approach compared with state of
the art, in terms of information loss, range query
distortion, and preserving temporal causality patterns.
Furthermore, our experiments demonstrate efficiency and
scalability on large-scale real and synthetic
datasets.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bellido:2013:CFP,
author = "Jesus Bellido and Rosa Alarc{\'o}n and Cesare
Pautasso",
title = "Control-Flow Patterns for Decentralized {RESTful}
Service Composition",
journal = j-TWEB,
volume = "8",
number = "1",
pages = "5:1--5:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2535911",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:23 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The REST architectural style has attracted a lot of
interest from industry due to the nonfunctional
properties it contributes to Web-based solutions.
SOAP/WSDL-based services, on the other hand, provide
tools and methodologies that allow the design and
development of software supporting complex service
arrangements, enabling complex business processes which
make use of well-known control-flow patterns. It is not
clear if and how such patterns should be modeled,
considering RESTful Web services that comply with the
statelessness, uniform interface and hypermedia
constraints. In this article, we analyze a set of
fundamental control-flow patterns in the context of
stateless compositions of RESTful services. We propose
a means of enabling their implementation using the HTTP
protocol and discuss the impact of our design choices
according to key REST architectural principles. We hope
to shed new light on the design of basic building
blocks for RESTful business processes.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Chelaru:2013:ADE,
author = "Sergiu Chelaru and Ismail Sengor Altingovde and Stefan
Siersdorfer and Wolfgang Nejdl",
title = "Analyzing, Detecting, and Exploiting Sentiment in
{Web} Queries",
journal = j-TWEB,
volume = "8",
number = "1",
pages = "6:1--6:??",
month = dec,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2535525",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Mar 13 08:28:23 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The Web contains an increasing amount of biased and
opinionated documents on politics, products, and
polarizing events. In this article, we present an
indepth analysis of Web search queries for
controversial topics, focusing on query sentiment. To
this end, we conduct extensive user assessments and
discriminative term analyses, as well as a sentiment
analysis using the SentiWordNet thesaurus, a lexical
resource containing sentiment annotations. Furthermore,
in order to detect the sentiment expressed in queries,
we build different classifiers based on query texts,
query result titles, and snippets. We demonstrate the
virtue of query sentiment detection in two different
use cases. First, we define a query recommendation
scenario that employs sentiment detection of results to
recommend additional queries for polarized queries
issued by search engine users. The second application
scenario is controversial topic discovery, where query
sentiment classifiers are employed to discover
previously unknown topics that trigger both highly
positive and negative opinions among the users of a
search engine. For both use cases, the results of our
evaluations on real-world data are promising and show
the viability and potential of query sentiment analysis
in practical scenarios.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Torres:2014:ASB,
author = "Sergio Duarte Torres and Ingmar Weber and Djoerd
Hiemstra",
title = "Analysis of Search and Browsing Behavior of Young
Users on the {Web}",
journal = j-TWEB,
volume = "8",
number = "2",
pages = "7:1--7:??",
month = mar,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2555595",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 1 05:42:19 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The Internet is increasingly used by young children
for all kinds of purposes. Nonetheless, there are not
many resources especially designed for children on the
Internet and most of the content online is designed for
grown-up users. This situation is problematic if we
consider the large differences between young users and
adults since their topic interests, computer skills,
and language capabilities evolve rapidly during
childhood. There is little research aimed at exploring
and measuring the difficulties that children encounter
on the Internet when searching for information and
browsing for content. In the first part of this work,
we employed query logs from a commercial search engine
to quantify the difficulties children of different ages
encounter on the Internet and to characterize the
topics that they search for. We employed query metrics
(e.g., the fraction of queries posed in natural
language), session metrics (e.g., the fraction of
abandoned sessions), and click activity (e.g., the
fraction of ad clicks). The search logs were also used
to retrace stages of child development. Concretely, we
looked for changes in interests (e.g., the distribution
of topics searched) and language development (e.g., the
readability of the content accessed and the vocabulary
size). In the second part of this work, we employed
toolbar logs from a commercial search engine to
characterize the browsing behavior of young users,
particularly to understand the activities on the
Internet that trigger search. We quantified the
proportion of browsing and search activity in the
toolbar sessions and we estimated the likelihood of a
user to carry out search on the Web vertical and
multimedia verticals (i.e., videos and images) given
that the previous event is another search event or a
browsing event. We observed that these metrics clearly
demonstrate an increased level of confusion and
unsuccessful search sessions among children. We also
found a clear relation between the reading level of the
clicked pages and characteristics of the users such as
age and educational attainment. In terms of browsing
behavior, children were found to start their activities
on the Internet with a search engine (instead of
directly browsing content) more often than adults. We
also observed a significantly larger amount of browsing
activity for the case of teenager users. Interestingly
we also found that if children visit knowledge-related
Web sites (i.e., information-dense pages such as
Wikipedia articles), they subsequently do more Web
searches than adults. Additionally, children and
especially teenagers were found to have a greater
tendency to engage in multimedia search, which calls to
improve the aggregation of multimedia results into the
current search result pages.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Su:2014:HIY,
author = "Ao-Jan Su and Y. Charlie Hu and Aleksandar Kuzmanovic
and Cheng-Kok Koh",
title = "How to Improve Your Search Engine Ranking: Myths and
Reality",
journal = j-TWEB,
volume = "8",
number = "2",
pages = "8:1--8:??",
month = mar,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2579990",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 1 05:42:19 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Search engines have greatly influenced the way people
access information on the Internet, as such engines
provide the preferred entry point to billions of pages
on the Web. Therefore, highly ranked Web pages
generally have higher visibility to people and pushing
the ranking higher has become the top priority for Web
masters. As a matter of fact, Search Engine
Optimization (SEO) has became a sizeable business that
attempts to improve their clients' ranking. Still, the
lack of ways to validate SEO's methods has created
numerous myths and fallacies associated with ranking
algorithms. In this article, we focus on two ranking
algorithms, Google's and Bing's, and design, implement,
and evaluate a ranking system to systematically
validate assumptions others have made about these
popular ranking algorithms. We demonstrate that linear
learning models, coupled with a recursive partitioning
ranking scheme, are capable of predicting ranking
results with high accuracy. As an example, we manage to
correctly predict 7 out of the top 10 pages for 78\% of
evaluated keywords. Moreover, for content-only ranking,
our system can correctly predict 9 or more pages out of
the top 10 ones for 77\% of search terms. We show how
our ranking system can be used to reveal the relative
importance of ranking features in a search engine's
ranking function, provide guidelines for SEOs and Web
masters to optimize their Web pages, validate or
disprove new ranking features, and evaluate search
engine ranking results for possible ranking bias.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Sirivianos:2014:LSF,
author = "Michael Sirivianos and Kyungbaek Kim and Jian Wei Gan
and Xiaowei Yang",
title = "Leveraging Social Feedback to Verify Online Identity
Claims",
journal = j-TWEB,
volume = "8",
number = "2",
pages = "9:1--9:??",
month = mar,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2543711",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 1 05:42:19 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Anonymity is one of the main virtues of the Internet,
as it protects privacy and enables users to express
opinions more freely. However, anonymity hinders the
assessment of the veracity of assertions that online
users make about their identity attributes, such as age
or profession. We propose FaceTrust, a system that uses
online social networks to provide lightweight identity
credentials while preserving a user's anonymity.
FaceTrust employs a ``game with a purpose'' design to
elicit the opinions of the friends of a user about the
user's self-claimed identity attributes, and uses
attack-resistant trust inference to assign veracity
scores to identity attribute assertions. FaceTrust
provides credentials, which a user can use to
corroborate his assertions. We evaluate our proposal
using a live Facebook deployment and simulations on a
crawled social graph. The results show that our
veracity scores are strongly correlated with the ground
truth, even when dishonest users make up a large
fraction of the social network and employ the Sybil
attack.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Pugliese:2014:EMM,
author = "Andrea Pugliese and Matthias Br{\"o}cheler and V. S.
Subrahmanian and Michael Ovelg{\"o}nne",
title = "Efficient {MultiView} Maintenance under Insertion in
Huge Social Networks",
journal = j-TWEB,
volume = "8",
number = "2",
pages = "10:1--10:??",
month = mar,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2541290",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 1 05:42:19 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Applications to monitor various aspects of social
networks are becoming increasingly popular. For
instance, marketers want to look for semantic patterns
relating to the content of tweets and Facebook posts
relating to their products. Law enforcement agencies
want to track behaviors involving potential criminals
on the Internet by looking for certain patterns of
behavior. Music companies want to track patterns of
spread of illegal music. These applications allow
multiple users to specify patterns of interest and
monitor them in real time as new data gets added to the
Web or to a social network. In this article we develop
the concept of social network view servers in which all
of these types of applications can be simultaneously
monitored. The patterns of interest are expressed as
views over an underlying graph or social network
database. We show that a given set of views can be
compiled in multiple possible ways to take advantage of
common substructures and define the concept of an
optimal merge. Though finding an optimal merge is shown
to be NP-hard, we develop the AddView to find very good
merges quickly. We develop a very fast MultiView
algorithm that scalably and efficiently maintains
multiple subgraph views when insertions are made to the
social network database. We show that our algorithm is
correct, study its complexity, and experimentally
demonstrate that our algorithm can scalably handle
updates to hundreds of views on 6 real-world social
network databases with up to 540M edges.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bislimovska:2014:TCB,
author = "Bojana Bislimovska and Alessandro Bozzon and Marco
Brambilla and Piero Fraternali",
title = "Textual and Content-Based Search in Repositories of
{Web} Application Models",
journal = j-TWEB,
volume = "8",
number = "2",
pages = "11:1--11:??",
month = mar,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2579991",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 1 05:42:19 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Model-driven engineering relies on collections of
models, which are the primary artifacts for software
development. To enable knowledge sharing and reuse,
models need to be managed within repositories, where
they can be retrieved upon users' queries. This article
examines two different techniques for indexing and
searching model repositories, with a focus on Web
development projects encoded in a domain-specific
language. Keyword-based and content-based search (also
known as query-by-example) are contrasted with respect
to the architecture of the system, the processing of
models and queries, and the way in which metamodel
knowledge can be exploited to improve search. A
thorough experimental evaluation is conducted to
examine what parameter configurations lead to better
accuracy and to offer an insight in what queries are
addressed best by each system.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bellogin:2014:NSW,
author = "Alejandro Bellog{\'\i}n and Pablo Castells and
Iv{\'a}n Cantador",
title = "Neighbor Selection and Weighting in User-Based
Collaborative Filtering: a Performance Prediction
Approach",
journal = j-TWEB,
volume = "8",
number = "2",
pages = "12:1--12:??",
month = mar,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2579993",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 1 05:42:19 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "User-based collaborative filtering systems suggest
interesting items to a user relying on similar-minded
people called neighbors. The selection and weighting of
these neighbors characterize the different
recommendation approaches. While standard strategies
perform a neighbor selection based on user
similarities, trust-aware recommendation algorithms
rely on other aspects indicative of user trust and
reliability. In this article we restate the trust-aware
recommendation problem, generalizing it in terms of
performance prediction techniques, whose goal is to
predict the performance of an information retrieval
system in response to a particular query. We
investigate how to adopt the preceding generalization
to define a unified framework where we conduct an
objective analysis of the effectiveness (predictive
power) of neighbor scoring functions. The proposed
framework enables discriminating whether recommendation
performance improvements are caused by the used
neighbor scoring functions or by the ways these
functions are used in the recommendation computation.
We evaluated our approach with several state-of-the-art
and novel neighbor scoring functions on three publicly
available datasets. By empirically comparing four
neighbor quality metrics and thirteen performance
predictors, we found strong predictive power for some
of the predictors with respect to certain metrics. This
result was then validated by checking the final
performance of recommendation strategies where
predictors are used for selecting and/or weighting user
neighbors. As a result, we have found that, by
measuring the predictive power of neighbor performance
predictors, we are able to anticipate which predictors
are going to perform better in neighbor-scoring-powered
versions of a user-based collaborative filtering
algorithm.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Qian:2014:FTD,
author = "Yi Qian and Sibel Adali",
title = "Foundations of Trust and Distrust in Networks:
Extended Structural Balance Theory",
journal = j-TWEB,
volume = "8",
number = "3",
pages = "13:1--13:??",
month = jun,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2628438",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 2 18:17:48 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Modeling trust in very large social networks is a hard
problem due to the highly noisy nature of these
networks that span trust relationships from many
different contexts, based on judgments of reliability,
dependability, and competence. Furthermore,
relationships in these networks vary in their level of
strength. In this article, we introduce a novel
extension of structural balance theory as a
foundational theory of trust and distrust in networks.
Our theory preserves the distinctions between trust and
distrust as suggested in the literature, but also
incorporates the notion of relationship strength that
can be expressed as either discrete categorical values,
as pairwise comparisons, or as metric distances. Our
model is novel, has sound social and psychological
basis, and captures the classical balance theory as a
special case. We then propose a convergence model,
describing how an imbalanced network evolves towards
new balance, and formulate the convergence problem of a
social network as a Metric Multidimensional Scaling
(MDS) optimization problem. Finally, we show how the
convergence model can be used to predict edge signs in
social networks and justify our theory through
extensive experiments on real datasets.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Soi:2014:CDC,
author = "Stefano Soi and Florian Daniel and Fabio Casati",
title = "Conceptual Development of Custom, Domain-Specific
Mashup Platforms",
journal = j-TWEB,
volume = "8",
number = "3",
pages = "14:1--14:??",
month = jun,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2628439",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 2 18:17:48 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Despite the common claim by mashup platforms that they
enable end-users to develop their own software, in
practice end-users still don't develop their own
mashups, as the highly technical or inexistent [sic]
user bases of today's mashup platforms testify. The key
shortcoming of current platforms is their
general-purpose nature, that privileges expressive
power over intuitiveness. In our prior work, we have
demonstrated that a domain-specific mashup approach,
which privileges intuitiveness over expressive power,
has much more potential to enable end-user development
(EUD). The problem is that developing mashup
platforms-domain-specific or not-is complex and time
consuming. In addition, domain-specific mashup
platforms by their very nature target only a small user
basis, that is, the experts of the target domain, which
makes their development not sustainable if it is not
adequately supported and automated. With this article,
we aim to make the development of custom,
domain-specific mashup platforms cost-effective. We
describe a mashup tool development kit (MDK) that is
able to automatically generate a mashup platform
(comprising custom mashup and component description
languages and design-time and runtime environments)
from a conceptual design and to provision it as a
service. We equip the kit with a dedicated development
methodology and demonstrate the applicability and
viability of the approach with the help of two case
studies.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zhang:2014:PBT,
author = "Xianchao Zhang and You Wang and Nan Mou and Wenxin
Liang",
title = "Propagating Both Trust and Distrust with Target
Differentiation for Combating Link-Based {Web} Spam",
journal = j-TWEB,
volume = "8",
number = "3",
pages = "15:1--15:??",
month = jun,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2628440",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 2 18:17:48 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Semi-automatic anti-spam algorithms propagate either
trust through links from a good seed set (e.g.,
TrustRank) or distrust through inverse links from a bad
seed set (e.g., Anti-TrustRank) to the entire Web.
These kinds of algorithms have shown their powers in
combating link-based Web spam since they integrate both
human judgement and machine intelligence. Nevertheless,
there is still much space for improvement. One issue of
most existing trust/distrust propagation algorithms is
that only trust or distrust is propagated and only a
good seed set or a bad seed set is used. According to
Wu et al. [2006a], a combined usage of both trust and
distrust propagation can lead to better results, and an
effective framework is needed to realize this insight.
Another more serious issue of existing algorithms is
that trust or distrust is propagated in nondifferential
ways, that is, a page propagates its trust or distrust
score uniformly to its neighbors, without considering
whether each neighbor should be trusted or distrusted.
Such kinds of blind propagating schemes are
inconsistent with the original intention of
trust/distrust propagation. However, it seems
impossible to implement differential propagation if
only trust or distrust is propagated. In this article,
we take the view that each Web page has both a
trustworthy side and an untrustworthy side, and we
thusly assign two scores to each Web page: T-Rank,
scoring the trustworthiness of the page, and D-Rank,
scoring the untrustworthiness of the page. We then
propose an integrated framework that propagates both
trust and distrust. In the framework, the propagation
of T-Rank/D-Rank is penalized by the target's current
D-Rank/T-Rank. In other words, the propagation of
T-Rank/D-Rank is decided by the target's current
(generalized) probability of being
trustworthy/untrustworthy; thus a page propagates more
trust/distrust to a trustworthy/untrustworthy neighbor
than to an untrustworthy/trustworthy neighbor. In this
way, propagating both trust and distrust with target
differentiation is implemented. We use T-Rank scores to
realize spam demotion and D-Rank scores to accomplish
spam detection. The proposed Trust-DistrustRank (TDR)
algorithm regresses to TrustRank and Anti-TrustRank
when the penalty factor is set to 1 and 0,
respectively. Thus TDR could be seen as a combinatorial
generalization of both TrustRank and Anti-TrustRank.
TDR not only makes full use of both trust and distrust
propagation, but also overcomes the disadvantages of
both TrustRank and Anti-TrustRank. Experimental results
on benchmark datasets show that TDR outperforms other
semi-automatic anti-spam algorithms for both spam
demotion and spam detection tasks under various
criteria.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Margaritis:2014:ITI,
author = "Giorgos Margaritis and Stergios V. Anastasiadis",
title = "Incremental Text Indexing for Fast Disk-Based Search",
journal = j-TWEB,
volume = "8",
number = "3",
pages = "16:1--16:??",
month = jun,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2560800",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 2 18:17:48 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Real-time search requires to incrementally ingest
content updates and almost immediately make them
searchable while serving search queries at low latency.
This is currently feasible for datasets of moderate
size by fully maintaining the index in the main memory
of multiple machines. Instead, disk-based methods for
incremental index maintenance substantially increase
search latency with the index fragmented across
multiple disk locations. For the support of fast search
over disk-based storage, we take a fresh look at
incremental text indexing in the context of current
architectural features. We introduce a greedy method
called Selective Range Flush (SRF) to contiguously
organize the index over disk blocks and dynamically
update it at low cost. We show that SRF requires
substantial experimental effort to tune specific
parameters for performance efficiency. Subsequently, we
propose the Unified Range Flush (URF) method, which is
conceptually simpler than SRF, achieves similar or
better performance with fewer parameters and less
tuning, and is amenable to I/O complexity analysis. We
implement interesting variations of the two methods in
the Proteus prototype search engine that we developed
and do extensive experiments with three different Web
datasets of size up to 1TB. Across different systems,
we show that our methods offer search latency that
matches or reduces up to half the lowest achieved by
existing disk-based methods. In comparison to an
existing method of comparable search latency on the
same system, our methods reduce by a factor of 2.0--2.4
the I/O part of build time and by 21--24\% the total
build time.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Siersdorfer:2014:AMC,
author = "Stefan Siersdorfer and Sergiu Chelaru and Jose {San
Pedro} and Ismail Sengor Altingovde and Wolfgang
Nejdl",
title = "Analyzing and Mining Comments and Comment Ratings on
the Social {Web}",
journal = j-TWEB,
volume = "8",
number = "3",
pages = "17:1--17:??",
month = jun,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2628441",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 2 18:17:48 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "An analysis of the social video sharing platform
YouTube and the news aggregator Yahoo! News reveals the
presence of vast amounts of community feedback through
comments for published videos and news stories, as well
as through metaratings for these comments. This article
presents an in-depth study of commenting and comment
rating behavior on a sample of more than 10 million
user comments on YouTube and Yahoo! News. In this
study, comment ratings are considered first-class
citizens. Their dependencies with textual content,
thread structure of comments, and associated content
(e.g., videos and their metadata) are analyzed to
obtain a comprehensive understanding of the community
commenting behavior. Furthermore, this article explores
the applicability of machine learning and data mining
to detect acceptance of comments by the community,
comments likely to trigger discussions, controversial
and polarizing content, and users exhibiting offensive
commenting behavior. Results from this study have
potential application in guiding the design of
community-oriented online discussion platforms.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Casteleyn:2014:TYR,
author = "Sven Casteleyn and Irene Garrig{\'o}s and
Jose-Norberto Maz{\'o}n",
title = "Ten Years of {Rich Internet Applications}: a
Systematic Mapping Study, and Beyond",
journal = j-TWEB,
volume = "8",
number = "3",
pages = "18:1--18:??",
month = jun,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2626369",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 2 18:17:48 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The term Rich Internet Applications (RIAs) is
generally associated with Web applications that provide
the features and functionality of traditional desktop
applications. Ten years after the introduction of the
term, an ample amount of research has been carried out
to study various aspects of RIAs. It has thus become
essential to summarize this research and provide an
adequate overview. OBJECTIVE. The objective of our
study is to assemble, classify, and analyze all RIA
research performed in the scientific community, thus
providing a consolidated overview thereof, and to
identify well-established topics, trends, and open
research issues. Additionally, we provide a qualitative
discussion of the most interesting findings. This work
therefore serves as a reference work for beginning and
established RIA researchers alike, as well as for
industrial actors that need an introduction in the
field, or seek pointers to (a specific subset of) the
state-of-the-art. METHOD. A systematic mapping study is
performed in order to identify all RIA-related
publications, define a classification scheme, and
categorize, analyze, and discuss the identified
research according to it. RESULTS. Our source
identification phase resulted in 133 relevant,
peer-reviewed publications, published between 2002 and
2011 in a wide variety of venues. They were
subsequently classified according to four facets:
development activity, research topic, contribution
type, and research type. Pie, stacked bar, and bubble
charts were used to depict and analyze the results. A
deeper analysis is provided for the most interesting
and/or remarkable results. CONCLUSION. Analysis of the
results shows that, although the RIA term was coined in
2002, the first RIA-related research appeared in 2004.
From 2007 there was a significant increase in research
activity, peaking in 2009 and decreasing to pre-2009
levels afterwards. All development phases are covered
in the identified research, with emphasis on ``design''
(33\%) and ``implementation'' (29\%). The majority of
research proposes a ``method'' (44\%), followed by
``model'' (22\%), ``methodology'' (18\%), and ``tools''
(16\%); no publications in the category ``metrics''
were found. The preponderant research topic is
``models, methods and methodologies'' (23\%) and, to a
lesser extent, ``usability and accessibility'' and
``user interface'' (11\% each). On the other hand, the
topic ``localization, internationalization and
multilinguality'' received no attention at all, and
topics such as ``deep Web'' (under 1\%), ``business
processing'', ``usage analysis'', ``data management'',
``quality and metrics'' (all under 2\%), ``semantics'',
and ``performance'' (slightly above 2\%) received very
little attention. Finally, there is a large majority of
``solution proposals'' (66\%), few ``evaluation
research'' (14\%), and even fewer ``validation'' (6\%),
although the latter have been increasing in recent
years.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Dincturk:2014:MBA,
author = "Mustafa Emre Dincturk and Guy-Vincent Jourdan and
Gregor V. Bochmann and Iosif Viorel Onut",
title = "A Model-Based Approach for Crawling {Rich Internet
Applications}",
journal = j-TWEB,
volume = "8",
number = "3",
pages = "19:1--19:??",
month = jun,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2626371",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 2 18:17:48 MDT 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "New Web technologies, like AJAX, result in more
responsive and interactive Web applications, sometimes
called Rich Internet Applications (RIAs). Crawling
techniques developed for traditional Web applications
are not sufficient for crawling RIAs. The inability to
crawl RIAs is a problem that needs to be addressed for
at least making RIAs searchable and testable. We
present a new methodology, called ``model-based
crawling'', that can be used as a basis to design
efficient crawling strategies for RIAs. We illustrate
model-based crawling with a sample strategy, called the
``hypercube strategy''. The performances of our
model-based crawling strategies are compared against
existing standard crawling strategies, including
breadth-first, depth-first, and a greedy strategy.
Experimental results show that our model-based crawling
approach is significantly more efficient than these
standard strategies.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Dragut:2014:MQR,
author = "Eduard C. Dragut and Bhaskar Dasgupta and Brian P.
Beirne and Ali Neyestani and Badr Atassi and Clement Yu
and Weiyi Meng",
title = "Merging Query Results From Local Search Engines for
Georeferenced Objects",
journal = j-TWEB,
volume = "8",
number = "4",
pages = "20:1--20:??",
month = oct,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2656344",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Nov 6 16:08:07 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The emergence of numerous online sources about local
services presents a need for more automatic yet
accurate data integration techniques. Local services
are georeferenced objects and can be queried by their
locations on a map, for instance, neighborhoods.
Typical local service queries (e.g., ``French
Restaurant in The Loop'') include not only information
about ``what'' (``French Restaurant'') a user is
searching for (such as cuisine) but also ``where''
information, such as neighborhood (``The Loop''). In
this article, we address three key problems: query
translation, result merging and ranking. Most local
search engines provide a (hierarchical) organization of
(large) cities into neighborhoods. A neighborhood in
one local search engine may correspond to sets of
neighborhoods in other local search engines. These make
the query translation challenging. To provide an
integrated access to the query results returned by the
local search engines, we need to combine the results
into a single list of results. Our contributions
include: (1) An integration algorithm for
neighborhoods. (2) A very effective business listing
resolution algorithm. (3) A ranking algorithm that
takes into consideration the user criteria, user
ratings and rankings. We have created a prototype
system, Yumi, over local search engines in the
restaurant domain. The restaurant domain is a
representative case study for the local services. We
conducted a comprehensive experimental study to
evaluate Yumi. A prototype version of Yumi is available
online.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Chen:2014:CCU,
author = "Xihui Chen and Jun Pang and Ran Xue",
title = "Constructing and Comparing User Mobility Profiles",
journal = j-TWEB,
volume = "8",
number = "4",
pages = "21:1--21:??",
month = oct,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2637483",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Nov 6 16:08:07 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Nowadays, the accumulation of people's whereabouts due
to location-based applications has made it possible to
construct their mobility profiles. This access to
users' mobility profiles subsequently brings benefits
back to location-based applications. For instance, in
on-line social networks, friends can be recommended not
only based on the similarity between their registered
information, for instance, hobbies and professions but
also referring to the similarity between their mobility
profiles. In this article, we propose a new approach to
construct and compare users' mobility profiles. First,
we improve and apply frequent sequential pattern mining
technologies to extract the sequences of places that a
user frequently visits and use them to model his
mobility profile. Second, we present a new method to
calculate the similarity between two users using their
mobility profiles. More specifically, we identify the
weaknesses of a similarity metric in the literature,
and propose a new one which not only fixes the
weaknesses but also provides more precise and effective
similarity estimation. Third, we consider the semantics
of spatio-temporal information contained in user
mobility profiles and add them into the calculation of
user similarity. It enables us to measure users'
similarity from different perspectives. Two specific
types of semantics are explored in this article:
location semantics and temporal semantics. Last, we
validate our approach by applying it to two real-life
datasets collected by Microsoft Research Asia and
Yonsei University, respectively. The results show that
our approach outperforms the existing works from
several aspects.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Vural:2014:SFW,
author = "A. Gural Vural and B. Barla Cambazoglu and Pinar
Karagoz",
title = "Sentiment-Focused {Web} Crawling",
journal = j-TWEB,
volume = "8",
number = "4",
pages = "22:1--22:??",
month = oct,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2644821",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Nov 6 16:08:07 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Sentiments and opinions expressed in Web pages towards
objects, entities, and products constitute an important
portion of the textual content available in the Web. In
the last decade, the analysis of such content has
gained importance due to its high potential for
monetization. Despite the vast interest in sentiment
analysis, somewhat surprisingly, the discovery of
sentimental or opinionated Web content is mostly
ignored. This work aims to fill this gap and addresses
the problem of quickly discovering and fetching the
sentimental content present in the Web. To this end, we
design a sentiment-focused Web crawling framework. In
particular, we propose different sentiment-focused Web
crawling strategies that prioritize discovered URLs
based on their predicted sentiment scores. Through
simulations, these strategies are shown to achieve
considerable performance improvement over
general-purpose Web crawling strategies in discovery of
sentimental Web content.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "22",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Kyusakov:2014:EFE,
author = "Rumen Kyusakov and Pablo Pu{\~n}al Pereira and Jens
Eliasson and Jerker Delsing",
title = "{EXIP}: a Framework for Embedded {Web} Development",
journal = j-TWEB,
volume = "8",
number = "4",
pages = "23:1--23:??",
month = oct,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2665068",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Nov 6 16:08:07 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Developing and deploying Web applications on networked
embedded devices is often seen as a way to reduce the
development cost and time to market for new target
platforms. However, the size of the messages and the
processing requirements of today's Web protocols, such
as HTTP and XML, are challenging for the most
resource-constrained class of devices that could also
benefit from Web connectivity. New Web protocols using
binary representations have been proposed for
addressing this issue. Constrained Application Protocol
(CoAP) reduces the bandwidth and processing
requirements compared to HTTP while preserving the core
concepts of the Web architecture. Similarly, Efficient
XML Interchange (EXI) format has been standardized for
reducing the size and processing time for XML
structured information. Nevertheless, the adoption of
these technologies is lagging behind due to lack of
support from Web browsers and current Web development
toolkits. Motivated by these problems, this article
presents the design and implementation techniques for
the EXIP framework for embedded Web development. The
framework consists of a highly efficient EXI processor,
a tool for EXI data binding based on templates, and a
CoAP/EXI/XHTML Web page engine. A prototype
implementation of the EXI processor is herein presented
and evaluated. It can be applied to Web browsers or
thin server platforms using XHTML and Web services for
supporting human-machine interactions in the Internet
of Things. This article contains four major results:
(1) theoretical and practical evaluation of the use of
binary protocols for embedded Web programming; (2) a
novel method for generation of EXI grammars based on
XML Schema definitions; (3) an algorithm for grammar
concatenation that produces normalized EXI grammars
directly, and hence reduces the number of iterations
during grammar generation; (4) an algorithm for
efficient representation of possible deviations from
the XML schema.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "23",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Thomas:2014:UID,
author = "Paul Thomas",
title = "Using Interaction Data to Explain Difficulty
Navigating Online",
journal = j-TWEB,
volume = "8",
number = "4",
pages = "24:1--24:??",
month = oct,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2656343",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Nov 6 16:08:07 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "A user's behaviour when browsing a Web site contains
clues to that user's experience. It is possible to
record some of these behaviours automatically, and
extract signals that indicate a user is having trouble
finding information. This allows for Web site analytics
based on user experiences, not just page impressions. A
series of experiments identified user browsing
behaviours-such as time taken and amount of scrolling
up a page-which predict navigation difficulty and which
can be recorded with minimal or no changes to existing
sites or browsers. In turn, patterns of page views
correlate with these signals and these patterns can
help Web authors understand where and why their sites
are hard to navigate. A new software tool, ``LATTE,''
automates this analysis and makes it available to Web
authors in the context of the site itself.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "24",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{White:2014:CBO,
author = "Ryen W. White and Ahmed Hassan",
title = "Content Bias in Online Health Search",
journal = j-TWEB,
volume = "8",
number = "4",
pages = "25:1--25:??",
month = oct,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2663355",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Nov 6 16:08:07 MST 2014",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Search engines help people answer consequential
questions. Biases in retrieved and indexed content
(e.g., skew toward erroneous outcomes that represent
deviations from reality), coupled with searchers'
biases in how they examine and interpret search
results, can lead people to incorrect answers. In this
article, we seek to better understand biases in search
and retrieval, and in particular those affecting the
accuracy of content in search results, including the
search engine index, features used for ranking, and the
formulation of search queries. Focusing on the
important domain of online health search, this research
broadens previous work on biases in search to examine
the role of search systems in contributing to biases.
To assess bias, we focus on questions about medical
interventions and employ reliable ground truth data
from authoritative medical sources. In the course of
our study, we utilize large-scale log analysis using
data from a popular Web search engine, deep probes of
result lists on that search engine, and crowdsourced
human judgments of search result captions and landing
pages. Our findings reveal bias in results, amplifying
searchers' existing biases that appear evident in their
search activity. We also highlight significant bias in
indexed content and show that specific ranking signals
and specific query terms support bias. Both of these
can degrade result accuracy and increase skewness in
search results. Our analysis has implications for bias
mitigation strategies in online search systems, and we
offer recommendations for search providers based on our
findings.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "25",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Fletcher:2015:EPN,
author = "Kenneth K. Fletcher and Xiaoqing F. Liu and Mingdong
Tang",
title = "Elastic Personalized Nonfunctional Attribute
Preference and Trade-off Based Service Selection",
journal = j-TWEB,
volume = "9",
number = "1",
pages = "1:1--1:??",
month = jan,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2697389",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 23 17:41:52 MST 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "For service users to get the best service that meet
their requirements, they prefer to personalize their
nonfunctional attributes, such as reliability and
price. However, the personalization makes it
challenging for service providers to completely meet
users' preferences, because they have to deal with
conflicting nonfunctional attributes when selecting
services for users. With this in mind, users may
sometimes want to explicitly specify their trade-offs
among nonfunctional attributes to make their
preferences known to service providers. In this
article, we present a novel service selection method
based on fuzzy logic that considers users' personalized
preferences and their trade-offs on nonfunctional
attributes during service selection. The method allows
users to represent their elastic nonfunctional
requirements and associated importance using linguistic
terms to specify their personalized trade-off
strategies. We present examples showing how the service
selection framework is used and a prototype with
real-world airline services to evaluate the proposed
framework's application.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zhang:2015:REA,
author = "Haibin Zhang and Yan Wang and Xiuzhen Zhang and
Ee-Peng Lim",
title = "{ReputationPro}: The Efficient Approaches to
Contextual Transaction Trust Computation in
{E}-Commerce Environments",
journal = j-TWEB,
volume = "9",
number = "1",
pages = "2:1--2:??",
month = jan,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2697390",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 23 17:41:52 MST 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In e-commerce environments, the trustworthiness of a
seller is utterly important to potential buyers,
especially when a seller is not known to them. Most
existing trust evaluation models compute a single value
to reflect the general trustworthiness of a seller
without taking any transaction context information into
account. With such a result as the indication of
reputation, a buyer may be easily deceived by a
malicious seller in a transaction where the notorious
value imbalance problem is involved-in other words, a
malicious seller accumulates a high-level reputation by
selling cheap products and then deceives buyers by
inducing them to purchase more expensive products. In
this article, we first present a trust vector
consisting of three values for contextual transaction
trust (CTT). In the computation of CTT values, three
identified important context dimensions, including
Product Category, Transaction Amount, and Transaction
Time, are taken into account. In the meantime, the
computation of each CTT value is based on both past
transactions and the forthcoming transaction. In
particular, with different parameters specified by a
buyer regarding context dimensions, different sets of
CTT values can be calculated. As a result, all of these
trust values can outline the reputation profile of a
seller that indicates the dynamic trustworthiness of a
seller in different products, product categories, price
ranges, time periods, and any necessary combination of
them. We name this new model ReputationPro.
Nevertheless, in ReputationPro, the computation of
reputation profile requires new data structures for
appropriately indexing the precomputation of aggregates
over large-scale ratings and transaction data in three
context dimensions, as well as novel algorithms for
promptly answering buyers' CTT queries. In addition,
storing precomputed aggregation results consumes a
large volume of space, particularly for a system with
millions of sellers. Therefore, reducing storage space
for aggregation results is also a great demand. To
solve these challenging problems, we first propose a
new index scheme CMK-tree by extending the
two-dimensional K-D-B-tree that indexes spatial data to
support efficient computation of CTT values. Then, we
further extend the CMK-tree and propose a
CMK-tree$^{RS}$ approach to reducing the storage space
allocated to each seller. The two approaches are not
only applicable to three context dimensions that are
either linear or hierarchical but also take into
account the characteristics of the transaction-time
model-that is, transaction data is inserted in
chronological order. Moreover, the proposed data
structures can index each specific product traded in a
time period to compute the trustworthiness of a seller
in selling a product. Finally, the experimental results
illustrate that the CMK-tree is superior in efficiency
of computing CTT values to all three existing
approaches in the literature. In particular, while
answering a buyer's CTT queries for each brand-based
product category, the CMK-tree has almost linear query
performance. In addition, with significantly reduced
storage space, the CMK-tree$^{RS}$ approach can further
improve the efficiency in computing CTT values.
Therefore, our proposed ReputationPro model is scalable
to large-scale e-commerce Web sites in terms of
efficiency and storage space consumption.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cai:2015:ALW,
author = "Wenbin Cai and Muhan Zhang and Ya Zhang",
title = "Active Learning for {Web} Search Ranking via Noise
Injection",
journal = j-TWEB,
volume = "9",
number = "1",
pages = "3:1--3:??",
month = jan,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2697391",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 23 17:41:52 MST 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Learning to rank has become increasingly important for
many information retrieval applications. To reduce the
labeling cost at training data preparation, many active
sampling algorithms have been proposed. In this
article, we propose a novel active learning-for-ranking
strategy called ranking-based sensitivity sampling
(RSS), which is tailored for Gradient Boosting Decision
Tree (GBDT), a machine-learned ranking method widely
used in practice by major commercial search engines for
ranking. We leverage the property of GBDT that samples
close to the decision boundary tend to be sensitive to
perturbations and design the active learning strategy
accordingly. We further theoretically analyze the
proposed strategy by exploring the connection between
the sensitivity used for sample selection and model
regularization to provide a potentially theoretical
guarantee w.r.t. the generalization capability.
Considering that the performance metrics of ranking
overweight the top-ranked items, item rank is
incorporated into the selection function. In addition,
we generalize the proposed technique to several other
base learners to show its potential applicability in a
wide variety of applications. Substantial experimental
results on both the benchmark dataset and a real-world
dataset have demonstrated that our proposed active
learning strategy is highly effective in selecting the
most informative examples.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Gill:2015:CWC,
author = "Phillipa Gill and Masashi Crete-Nishihata and Jakub
Dalek and Sharon Goldberg and Adam Senft and Greg
Wiseman",
title = "Characterizing {Web} Censorship Worldwide: Another
Look at the {OpenNet} Initiative Data",
journal = j-TWEB,
volume = "9",
number = "1",
pages = "4:1--4:??",
month = jan,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2700339",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 23 17:41:52 MST 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In this study, we take another look at 5 years of web
censorship data gathered by the OpenNet Initiative in
77 countries using user-based testing with locally
relevant content. Prior to our work, this data had been
analyzed with little automation, focusing on what
content had been blocked, rather than how blocking was
carried out. In this study, we use more rigorous
automation to obtain a longitudinal, global view of the
technical means used for web censorship. We also
identify blocking that had been missed in prior
analyses. Our results point to considerable variability
in the technologies used for web censorship, across
countries, time, and types of content, and even across
ISPs in the same country. In addition to characterizing
web censorship in countries that, thus far, have eluded
technical analysis, we also discuss the implications of
our observations on the design of future network
measurement platforms and circumvention technologies.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Fionda:2015:NFL,
author = "Valeria Fionda and Giuseppe Pirr{\`o} and Claudio
Gutierrez",
title = "{NautiLOD}: a Formal Language for the {Web of Data}
Graph",
journal = j-TWEB,
volume = "9",
number = "1",
pages = "5:1--5:??",
month = jan,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2697393",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 23 17:41:52 MST 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The Web of Linked Data is a huge graph of distributed
and interlinked datasources fueled by structured
information. This new environment calls for formal
languages and tools to automatize navigation across
datasources (nodes in such graph) and enable
semantic-aware and Web-scale search mechanisms. In this
article we introduce a declarative navigational
language for the Web of Linked Data graph called N
autiLOD. NautiLOD enables one to specify datasources
via the intertwining of navigation and querying
capabilities. It also features a mechanism to specify
actions (e.g., send notification messages) that obtain
their parameters from datasources reached during the
navigation. We provide a formalization of the NautiLOD
semantics, which captures both nodes and fragments of
the Web of Linked Data. We present algorithms to
implement such semantics and study their computational
complexity. We discuss an implementation of the
features of NautiLOD in a tool called swget, which
exploits current Web technologies and protocols. We
report on the evaluation of swget and its comparison
with related work. Finally, we show the usefulness of
capturing Web fragments by providing examples in
different knowledge domains.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Anonymous:2015:E,
author = "Anonymous",
title = "Editorial",
journal = j-TWEB,
volume = "9",
number = "2",
pages = "6:1--6:??",
month = may,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2755995",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 27 10:18:18 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Tranquillini:2015:MEI,
author = "Stefano Tranquillini and Florian Daniel and Pavel
Kucherbaev and Fabio Casati",
title = "Modeling, Enacting, and Integrating Custom
Crowdsourcing Processes",
journal = j-TWEB,
volume = "9",
number = "2",
pages = "7:1--7:??",
month = may,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2746353",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 27 10:18:18 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Crowdsourcing (CS) is the outsourcing of a unit of
work to a crowd of people via an open call for
contributions. Thanks to the availability of online CS
platforms, such as Amazon Mechanical Turk or
CrowdFlower, the practice has experienced a tremendous
growth over the past few years and demonstrated its
viability in a variety of fields, such as data
collection and analysis or human computation. Yet it is
also increasingly struggling with the inherent
limitations of these platforms: each platform has its
own logic of how to crowdsource work (e.g., marketplace
or contest), there is only very little support for
structured work (work that requires the coordination of
multiple tasks), and it is hard to integrate
crowdsourced tasks into state-of-the-art business
process management (BPM) or information systems. We
attack these three shortcomings by (1) developing a
flexible CS platform (we call it Crowd Computer, or CC)
that allows one to program custom CS logics for
individual and structured tasks, (2) devising a
BPMN--based modeling language that allows one to
program CC intuitively, (3) equipping the language with
a dedicated visual editor, and (4) implementing CC on
top of standard BPM technology that can easily be
integrated into existing software and processes. We
demonstrate the effectiveness of the approach with a
case study on the crowd-based mining of mashup model
patterns.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Diaz:2015:AWR,
author = "Oscar D{\'\i}az and Crist{\'o}bal Arellano",
title = "The Augmented {Web}: Rationales, Opportunities, and
Challenges on Browser-Side Transcoding",
journal = j-TWEB,
volume = "9",
number = "2",
pages = "8:1--8:??",
month = may,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2735633",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 27 10:18:18 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Today's web personalization technologies use
approaches like user categorization, configuration, and
customization but do not fully support individualized
requirements. As a significant portion of our social
and working interactions are migrating to the web, we
can expect an increase in these kinds of minority
requirements. Browser-side transcoding holds the
promise of facilitating this aim by opening
personalization to third parties through web
augmentation (WA), realized in terms of extensions and
userscripts. WA is to the web what augmented reality is
to the physical world: to layer relevant
content/layout/navigation over the existing web to
improve the user experience. From this perspective, WA
is not as powerful as web personalization since its
scope is limited to the surface of the web. However, it
permits this surface to be tuned by developers other
than the sites' webmasters. This opens up the web to
third parties who might come up with imaginative ways
of adapting the web surface for their own purposes. Its
success is backed up by millions of downloads. This
work looks at this phenomenon, delving into the
``what,'' the ``why,'' and the ``what for'' of WA, and
surveys the challenges ahead for WA to thrive. To this
end, we appraise the most downloaded 45 WA extensions
for Mozilla Firefox and Google Chrome as well as
conduct a systematic literature review to identify what
quality issues received the most attention in the
literature. The aim is to raise awareness about WA as a
key enabler of the personal web and point out research
directions.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Sun:2015:ITB,
author = "Chang-Ai Sun and Xin Zhang and Yan Shang and Marco
Aiello",
title = "Integrating Transactions into {BPEL} Service
Compositions: an Aspect-Based Approach",
journal = j-TWEB,
volume = "9",
number = "2",
pages = "9:1--9:??",
month = may,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2757288",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 27 10:18:18 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The concept of software as a service has been
increasingly adopted to develop distributed
applications. Ensuring the reliability of loosely
coupled compositions is a challenging task because of
the open, dynamic, and independent nature of composable
services; this is especially true when the execution of
a service-based process relies on independent but
correlated services. Transactions are the prototypical
case of compositions spanning across multiple services
and needing properties to be valid throughout the whole
execution. Although transaction protocols and service
composition languages have been proposed in the past
decade, a true viable and effective solution is still
missing. In this article, we propose a systematic
aspect-based approach to integrating transactions into
service compositions, taking into account the
well-known protocols: Web Service Transaction and
Business Process Execution Language (BPEL). In our
approach, transaction policies are first defined as a
set of aspects. They are then converted to standard
BPEL elements. Finally, these transaction-related
elements and the original BPEL process are weaved
together, resulting in a transactional executable BPEL
process. At runtime, transaction management is the
responsibility of a middleware, which implements the
coordination framework and transaction protocols
followed by the transactional BPEL process and
transaction-aware Web services. To automate the
proposed approach, we developed a supporting platform
called Salan to aid the tasks of defining, validating,
and weaving aspect-based transaction policies, and of
deploying the transactional BPEL processes. By means of
a case study, we demonstrate the proposed approach and
evaluate the performance of the supporting platform.
Experimental results show that this approach is
effective in producing reliable business processes
while reducing the need for direct human involvement.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Kwasnikowska:2015:FAO,
author = "Natalia Kwasnikowska and Luc Moreau and Jan {Van Den
Bussche}",
title = "A Formal Account of the Open Provenance Model",
journal = j-TWEB,
volume = "9",
number = "2",
pages = "10:1--10:??",
month = may,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2734116",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 27 10:18:18 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "On the Web, where resources such as documents and data
are published, shared, transformed, and republished,
provenance is a crucial piece of metadata that would
allow users to place their trust in the resources they
access. The open provenance model (OPM) is a community
data model for provenance that is designed to
facilitate the meaningful interchange of provenance
information between systems. Underpinning OPM is a
notion of directed graph, where nodes represent data
products and processes involved in past computations
and edges represent dependencies between them; it is
complemented by graphical inference rules allowing new
dependencies to be derived. Until now, however, the OPM
model was a purely syntactical endeavor. The present
article extends OPM graphs with an explicit distinction
between precise and imprecise edges. Then a formal
semantics for the thus enriched OPM graphs is proposed,
by viewing OPM graphs as temporal theories on the
temporal events represented in the graph. The original
OPM inference rules are scrutinized in view of the
semantics and found to be sound but incomplete. An
extended set of graphical rules is provided and proved
to be complete for inference. The article concludes
with applications of the formal semantics to
inferencing in OPM graphs, operators on OPM graphs, and
a formal notion of refinement among OPM graphs.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cappiello:2015:UCA,
author = "Cinzia Cappiello and Maristella Matera and Matteo
Picozzi",
title = "A {UI}-Centric Approach for the End-User Development
of Multidevice Mashups",
journal = j-TWEB,
volume = "9",
number = "3",
pages = "11:1--11:??",
month = jun,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2735632",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Aug 7 10:27:41 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In recent years, models, composition paradigms, and
tools for mashup development have been proposed to
support the integration of information sources,
services and APIs available on the Web. The challenge
is to provide a gate to a ``programmable Web,'' where
end users are allowed to construct easily composite
applications that merge content and functions so as to
satisfy the long tail of their specific needs. The
approaches proposed so far do not fully accommodate
this vision. This article, therefore, proposes a mashup
development framework that is oriented toward the
End-User Development. Given the fundamental role of
user interfaces (UIs) as a medium easily understandable
by the end users, the proposed approach is
characterized by UI-centric models able to support a
WYSIWYG (What You See Is What You Get) specification of
data integration and service orchestration. It,
therefore, contributes to the definition of adequate
abstractions that, by hiding the technology and
implementation complexity, can be adopted by the end
users in a kind of ``democratic'' paradigm for mashup
development. This article also shows how model-to-code
generative techniques translate models into application
schemas, which in turn guide the dynamic instantiation
of the composite applications at runtime. This is
achieved through lightweight execution environments
that can be deployed on the Web and on mobile devices
to support the pervasive use of the created
applications.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zafar:2015:SCO,
author = "Muhammad Bilal Zafar and Parantapa Bhattacharya and
Niloy Ganguly and Krishna P. Gummadi and Saptarshi
Ghosh",
title = "Sampling Content from Online Social Networks:
Comparing Random vs. Expert Sampling of the {Twitter}
Stream",
journal = j-TWEB,
volume = "9",
number = "3",
pages = "12:1--12:??",
month = jun,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2743023",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Aug 7 10:27:41 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Analysis of content streams gathered from social
networking sites such as Twitter has several
applications ranging from content search and
recommendation, news detection to business analytics.
However, processing large amounts of data generated on
these sites in real-time poses a difficult challenge.
To cope with the data deluge, analytics companies and
researchers are increasingly resorting to sampling. In
this article, we investigate the crucial question of
how to sample content streams generated by users in
online social networks. The traditional method is to
randomly sample all the data. For example, most studies
using Twitter data today rely on the 1\% and 10\%
randomly sampled streams of tweets that are provided by
Twitter. In this paper, we analyze a different sampling
methodology, one where content is gathered only from a
relatively small sample ($< 1\%$) of the user
population, namely, the expert users. Over the duration
of a month, we gathered tweets from over 500,000
Twitter users who are identified as experts on a
diverse set of topics, and compared the resulting
expert sampled tweets with the 1\% randomly sampled
tweets provided publicly by Twitter. We compared the
sampled datasets along several dimensions, including
the popularity, topical diversity, trustworthiness, and
timeliness of the information contained within them,
and on the sentiment/opinion expressed on specific
topics. Our analysis reveals several important
differences in data obtained through the different
sampling methodologies, which have serious implications
for applications such as topical search, trustworthy
content recommendations, breaking news detection, and
opinion mining.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wang:2015:SWU,
author = "Yazhe Wang and Jamie Callan and Baihua Zheng",
title = "Should We Use the Sample? {Analyzing} Datasets Sampled
from {Twitter}'s Stream {API}",
journal = j-TWEB,
volume = "9",
number = "3",
pages = "13:1--13:??",
month = jun,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2746366",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Aug 7 10:27:41 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Researchers have begun studying content obtained from
microblogging services such as Twitter to address a
variety of technological, social, and commercial
research questions. The large number of Twitter users
and even larger volume of tweets often make it
impractical to collect and maintain a complete record
of activity; therefore, most research and some
commercial software applications rely on samples, often
relatively small samples, of Twitter data. For the most
part, sample sizes have been based on availability and
practical considerations. Relatively little attention
has been paid to how well these samples represent the
underlying stream of Twitter data. To fill this gap,
this article performs a comparative analysis on samples
obtained from two of Twitter's streaming APIs with a
more complete Twitter dataset to gain an in-depth
understanding of the nature of Twitter data samples and
their potential for use in various data mining tasks.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Su:2015:RRT,
author = "Zhiyuan Su and Ling Liu and Mingchu Li and Xinxin Fan
and Yang Zhou",
title = "Reliable and Resilient Trust Management in Distributed
Service Provision Networks",
journal = j-TWEB,
volume = "9",
number = "3",
pages = "14:1--14:??",
month = jun,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2754934",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Aug 7 10:27:41 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Distributed service networks are popular platforms for
service providers to offer services to consumers and
for service consumers to acquire services from unknown
parties. eBay and Amazon are two well-known examples of
enabling and hosting such service networks to connect
service providers to service consumers. Trust
management is a critical component for scaling such
distributed service networks to a large and growing
number of participants. In this article, we present
ServiceTrust$^{++}$, a feedback quality--sensitive and
attack resilient trust management scheme for empowering
distributed service networks with effective trust
management capability. Compared with existing trust
models, ServiceTrust$^{++}$ has several novel features.
First, we present six attack models to capture both
independent and colluding attacks with malicious
cliques, malicious spies, and malicious camouflages.
Second, we aggregate the feedback ratings based on the
variances of participants' feedback behaviors and
incorporate feedback similarity as weight into the
local trust algorithm. Third, we compute the global
trust of a participant by employing conditional trust
propagation based on the feedback similarity threshold.
This allows ServiceTrust$^{++}$ to control and prevent
malicious spies and malicious camouflage peers from
boosting their global trust scores by manipulating the
feedback ratings of good peers and by taking advantage
of the uniform trust propagation. Finally, we
systematically combine a trust-decaying strategy with a
threshold value--based conditional trust propagation to
further strengthen the robustness of our global trust
computation against sophisticated malicious feedback.
Experimental evaluation with both simulation-based
networks and real network dataset Epinion show that
ServiceTrust$^{++}$ is highly resilient against all six
attack models and highly effective compared to
EigenTrust, the most popular and representative trust
propagation model to date.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Calzavara:2015:SLA,
author = "Stefano Calzavara and Gabriele Tolomei and Andrea
Casini and Michele Bugliesi and Salvatore Orlando",
title = "A Supervised Learning Approach to Protect Client
Authentication on the {Web}",
journal = j-TWEB,
volume = "9",
number = "3",
pages = "15:1--15:??",
month = jun,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2754933",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Aug 7 10:27:41 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Browser-based defenses have recently been advocated as
an effective mechanism to protect potentially insecure
web applications against the threats of session
hijacking, fixation, and related attacks. In existing
approaches, all such defenses ultimately rely on
client-side heuristics to automatically detect cookies
containing session information, to then protect them
against theft or otherwise unintended use. While
clearly crucial to the effectiveness of the resulting
defense mechanisms, these heuristics have not, as yet,
undergone any rigorous assessment of their adequacy. In
this article, we conduct the first such formal
assessment, based on a ground truth of 2,464 cookies we
collect from 215 popular websites of the Alexa ranking.
To obtain the ground truth, we devise a semiautomatic
procedure that draws on the novel notion of
authentication token, which we introduce to capture
multiple web authentication schemes. We test existing
browser-based defenses in the literature against our
ground truth, unveiling several pitfalls both in the
heuristics adopted and in the methods used to assess
them. We then propose a new detection method based on
supervised learning, where our ground truth is used to
train a set of binary classifiers, and report on
experimental evidence that our method outperforms
existing proposals. Interestingly, the resulting
classifiers, together with our hands-on experience in
the construction of the ground truth, provide new
insight on how web authentication is actually
implemented in practice.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Lee:2015:DPM,
author = "Sihyung Lee",
title = "Detection of Political Manipulation in Online
Communities through Measures of Effort and
Collaboration",
journal = j-TWEB,
volume = "9",
number = "3",
pages = "16:1--16:??",
month = jun,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2767134",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Aug 7 10:27:41 MDT 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Online social media allow users to interact with one
another by sharing opinions, and these opinions have a
critical impact on the way readers think and behave.
Accordingly, an increasing number of {$<$ i$>$
manipulators$<$}/{i$>$} deliberately spread messages to
influence the public, often in an organized manner. In
particular, political manipulation-manipulation of
opponents to win political advantage-can result in
serious consequences: antigovernment riots can break
out, leading to candidates' defeat in an election. A
few approaches have been proposed to detect such
manipulation based on the level of social interaction
(i.e., manipulators actively post opinions but
infrequently befriend and reply to other users).
However, several studies have shown that the
interactions can be forged at a low cost and thus may
not be effective measures of manipulation. To go one
step further, we collect a dataset for real,
large-scale political manipulation, which consists of
opinions found on Internet forums. These opinions are
divided into manipulators and nonmanipulators. Using
this collection, we demonstrate that manipulators
inevitably work hard, in teams, to quickly influence a
large audience. With this in mind, it could be said
that a high level of collaborative efforts strongly
indicates manipulation. For example, a group of
manipulators may jointly post numerous opinions with a
consistent theme and selectively recommend the same,
well-organized opinion to promote its rank. We show
that the effort measures, when combined with a
supervised learning algorithm, successfully identify
greater than 95\% of the manipulators. We believe that
the proposed method will help system administrators to
accurately detect manipulators in disguise,
significantly decreasing the intensity of
manipulation.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Gollapalli:2015:IRH,
author = "Sujatha Das Gollapalli and Cornelia Caragea and
Prasenjit Mitra and C. Lee Giles",
title = "Improving Researcher Homepage Classification with
Unlabeled Data",
journal = j-TWEB,
volume = "9",
number = "4",
pages = "17:1--17:??",
month = oct,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2767135",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 25 07:43:09 MST 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/hash.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "A classifier that determines if a webpage is relevant
to a specified set of topics comprises a key component
for focused crawling. Can a classifier that is tuned to
perform well on training datasets continue to filter
out irrelevant pages in the face of changing content on
the Web? We investigate this question in the context of
identifying researcher homepages. We show
experimentally that classifiers trained on existing
datasets of academic homepages underperform on
``non-homepages'' present on current-day academic
websites. As an alternative to obtaining labeled
datasets to retrain classifiers for the new content, in
this article we ask the following question: ``How can
we effectively use the unlabeled data readily available
from academic websites to improve researcher homepage
classification?'' We design novel URL-based features
and use them in conjunction with content-based features
for representing homepages. Within the co-training
framework, these sets of features can be treated as
complementary views enabling us to effectively use
unlabeled data and obtain remarkable improvements in
homepage identification on the current-day academic
websites. We also propose a novel technique for
``learning a conforming pair of classifiers'' that
mimics co-training. Our algorithm seeks to minimize a
loss (objective) function quantifying the difference in
predictions from the two views afforded by co-training.
We argue that this loss formulation provides insights
for understanding co-training and can be used even in
the absence of a validation dataset. Our next set of
findings pertains to the evaluation of other
state-of-the-art techniques for classifying homepages.
First, we apply feature selection (FS) and feature
hashing (FH) techniques independently and in
conjunction with co-training to academic homepages. FS
is a well-known technique for removing redundant and
unnecessary features from the data representation,
whereas FH is a technique that uses hash functions for
efficient encoding of features. We show that FS can be
effectively combined with co-training to obtain further
improvements in identifying homepages. However, using
hashed feature representations, a performance
degradation is observed possibly due to feature
collisions. Finally, we evaluate other semisupervised
algorithms for homepage classification. We show that
although several algorithms are effective in using
information from the unlabeled instances, co-training
that explicitly harnesses the feature split in the
underlying instances outperforms approaches that
combine content and URL features into a single view.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wang:2015:DCU,
author = "Jing Wang and Clement T. Yu and Philip S. Yu and Bing
Liu and Weiyi Meng",
title = "Diversionary Comments under Blog Posts",
journal = j-TWEB,
volume = "9",
number = "4",
pages = "18:1--18:??",
month = oct,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2789211",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 25 07:43:09 MST 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "There has been a recent swell of interest in the
analysis of blog comments. However, much of the work
focuses on detecting comment spam in the blogsphere. An
important issue that has been neglected so far is the
identification of diversionary comments. Diversionary
comments are defined as comments that divert the topic
from the original post. A possible purpose is to
distract readers from the original topic and draw
attention to a new topic. We categorize diversionary
comments into five types based on our observations and
propose an effective framework to identify and flag
them. To the best of our knowledge, the problem of
detecting diversionary comments has not been studied so
far. We solve the problem in two different ways: (i)
rank all comments in descending order of being
diversionary and (ii) consider it as a classification
problem. Our evaluation on 4,179 comments under 40
different blog posts from Digg and Reddit shows that
the proposed method achieves the high mean average
precision of 91.9\% when the problem is considered as a
ranking problem and 84.9\% of F-measure as a
classification problem. Sensitivity analysis indicates
that the effectiveness of the method is stable under
different parameter settings.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Katzir:2015:ECC,
author = "Liran Katzir and Stephen J. Hardiman",
title = "Estimating Clustering Coefficients and Size of Social
Networks via Random Walk",
journal = j-TWEB,
volume = "9",
number = "4",
pages = "19:1--19:??",
month = oct,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2790304",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 25 07:43:09 MST 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This work addresses the problem of estimating social
network measures. Specifically, the measures at hand
are the network average and global clustering
coefficients and the number of registered users. The
algorithms at hand (1) assume no prior knowledge about
the network and (2) access the network using only the
publicly available interface. More precisely, this work
provides (a) a unified approach for clustering
coefficients estimation and (b) a new network size
estimator. The unified approach for the clustering
coefficients yields the first external access algorithm
for estimating the global clustering coefficient. The
new network size estimator offers improved accuracy
compared to prior art estimators. Our approach is to
view a social network as an undirected graph and use
the public interface to retrieve a random walk. To
estimate the clustering coefficient, the connectivity
of each node in the random walk sequence is tested in
turn. We show that the error drops exponentially in the
number of random walk steps. For the network size
estimation we offer a generalized view of prior art
estimators that in turn yields an improved estimator.
All algorithms are validated on several publicly
available social network datasets.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Watanabe:2015:FQM,
author = "Willian Massami Watanabe and Ana Luiza Dias and Renata
Pontin {De Mattos Fortes}",
title = "{Fona}: Quantitative Metric to Measure Focus
Navigation on Rich {Internet} Applications",
journal = j-TWEB,
volume = "9",
number = "4",
pages = "20:1--20:??",
month = oct,
year = "2015",
CODEN = "????",
DOI = "https://doi.org/10.1145/2812812",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 25 07:43:09 MST 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The Web 2.0 brought new requirements to the
architecture of web systems. Web applications'
interfaces are becoming more and more interactive.
However, these changes are severely impacting how
disabled users interact through assistive technologies
with the web. In order to deploy an accessible web
application, developers can use WAI-ARIA to design an
accessible web application, which manually implements
focus and keyboard navigation mechanisms. This article
presents a quantitative metric, named Fona, which
measures how the Focus Navigation WAI-ARIA requirement
has been implemented on the web. Fona counts JavaScript
mouse event listeners, HTML elements with role
attributes, and TabIndex attributes in the DOM
structure of webpages. Fona's evaluation approach
provides a narrow analysis of one single accessibility
requirement. But it enables monitoring this
accessibility requirement in a large number of
webpages. This monitoring activity might be used to
give insights about how Focus Navigation and ARIA
requirements have been considered by web development
teams. Fona is validated comparing the results of a set
of WAI-ARIA conformant implementations and a set of
webpages formed by Alexa's 349 top most popular
websites. The analysis of Fona's value for Alexa's
websites highlights that many websites still lack the
implementation of Focus Navigation through their
JavaScript interactive content.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Marszalkowski:2016:ASC,
author = "Jakub Marszalkowski and Jan Mizgajski and Dariusz
Mokwa and Maciej Drozdowski",
title = "Analysis and Solution of {CSS}-Sprite Packing
Problem",
journal = j-TWEB,
volume = "10",
number = "1",
pages = "1:1--1:??",
month = feb,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2818377",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "A CSS-sprite packing problem is considered in this
article. CSS-sprite is a technique of combining many
pictures of a web page into one image for the purpose
of reducing network transfer time. The CSS-sprite
packing problem is formulated here as an optimization
challenge. The significance of geometric packing, image
compression and communication performance is discussed.
A mathematical model for constructing multiple sprites
and optimization of load time is proposed. The impact
of PNG-sprite aspect ratio on file size is studied
experimentally. Benchmarking of real user web browsers
communication performance covers latency, bandwidth,
number of concurrent channels as well as speedup from
parallel download. Existing software for building
CSS-sprites is reviewed. A novel method, called
Spritepack, is proposed and evaluated. Spritepack
outperforms current software.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Amor:2016:DBT,
author = "Iheb Ben Amor and Salima Benbernou and Mourad Ouziri
and Zaki Malik and Brahim Medjahed",
title = "Discovering Best Teams for Data Leak-Aware
Crowdsourcing in Social Networks",
journal = j-TWEB,
volume = "10",
number = "1",
pages = "2:1--2:??",
month = feb,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2814573",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Crowdsourcing is emerging as a powerful paradigm to
help perform a wide range of tedious tasks in various
enterprise applications. As such applications become
more complex, crowdsourcing systems often require the
collaboration of several experts connected through
professional/social networks and organized in various
teams. For instance, a well-known car manufacturer
asked fans to contribute ideas for the kinds of
technologies that should be incorporated into one of
its cars. For that purpose, fans needed to collaborate
and form teams competing with each others to come up
with the best ideas. However, once teams are formed,
each one would like to provide the best solution and
treat that solution as a ``trade secret,'' hence
preventing any data leak to its competitors (i.e., the
other teams). In this article, we propose a data
leak--aware crowdsourcing system called SocialCrowd. We
introduce a clustering algorithm that uses social
relationships between crowd workers to discover all
possible teams while avoiding interteam data leakage.
We also define a ranking mechanism to select the
``best'' team configurations. Our mechanism is based on
the semiring approach defined in the area of soft
constraints programming. Finally, we present
experiments to assess the efficiency of the proposed
approach.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Song:2016:IJV,
author = "Hengjie Song and Yonghui Xu and Huaqing Min and
Qingyao Wu and Wei Wei and Jianshu Weng and Xiaogang
Han and Qiang Yang and Jialiang Shi and Jiaqian Gu and
Chunyan Miao and Nishida Toyoaki",
title = "Individual Judgments Versus Consensus: Estimating
Query-{URL} Relevance",
journal = j-TWEB,
volume = "10",
number = "1",
pages = "3:1--3:??",
month = feb,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2834122",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Query-URL relevance, measuring the relevance of each
retrieved URL with respect to a given query, is one of
the fundamental criteria to evaluate the performance of
commercial search engines. The traditional way to
collect reliable and accurate query-URL relevance
requires multiple annotators to provide their
individual judgments based on their subjective
expertise (e.g., understanding of user intents). In
this case, the annotators' subjectivity reflected in
each annotator individual judgment (AIJ) inevitably
affects the quality of the ground truth relevance
(GTR). But to the best of our knowledge, the potential
impact of AIJs on estimating GTRs has not been studied
and exploited quantitatively by existing work. This
article first studies how multiple AIJs and GTRs are
correlated. Our empirical studies find that the
multiple AIJs possibly provide more cues to improve the
accuracy of estimating GTRs. Inspired by this finding,
we then propose a novel approach to integrating the
multiple AIJs with the features characterizing
query-URL pairs for estimating GTRs more accurately.
Furthermore, we conduct experiments in a commercial
search engine-Baidu.com-and report significant gains in
terms of the normalized discounted cumulative gains.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zhang:2016:DSP,
author = "Xianchao Zhang and Zhaoxing Li and Shaoping Zhu and
Wenxin Liang",
title = "Detecting Spam and Promoting Campaigns in {Twitter}",
journal = j-TWEB,
volume = "10",
number = "1",
pages = "4:1--4:??",
month = feb,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2846102",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Twitter has become a target platform for both
promoters and spammers to disseminate their messages,
which are more harmful than traditional spamming
methods, such as email spamming. Recently, large
amounts of campaigns that contain lots of spam or
promotion accounts have emerged in Twitter. The
campaigns cooperatively post unwanted information, and
thus they can infect more normal users than individual
spam or promotion accounts. Organizing or participating
in campaigns has become the main technique to spread
spam or promotion information in Twitter. Since
traditional solutions focus on checking individual
accounts or messages, efficient techniques for
detecting spam and promotion campaigns in Twitter are
urgently needed. In this article, we propose a
framework to detect both spam and promotion campaigns.
Our framework consists of three steps: the first step
links accounts who post URLs for similar purposes; the
second step extracts candidate campaigns that may be
for spam or promotion purposes; and the third step
classifies the candidate campaigns into normal, spam,
and promotion groups. The key point of the framework is
how to measure the similarity between accounts'
purposes of posting URLs. We present two measure
methods based on Shannon information theory: the first
one uses the URLs posted by the users, and the second
one considers both URLs and timestamps. Experimental
results demonstrate that the proposed methods can
extract the majority of the candidate campaigns
correctly, and detect promotion and spam campaigns with
high precision and recall.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Eshuis:2016:FCE,
author = "Rik Eshuis and Freddy L{\'e}cu{\'e} and Nikolay
Mehandjiev",
title = "Flexible Construction of Executable Service
Compositions from Reusable Semantic Knowledge",
journal = j-TWEB,
volume = "10",
number = "1",
pages = "5:1--5:??",
month = feb,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2842628",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Most service composition approaches rely on top-down
decomposition of a problem and AI-style planning to
assemble service components into a meaningful whole,
impeding reuse and flexibility. In this article, we
propose an approach that starts from declarative
knowledge about the semantics of individual service
components and algorithmically constructs a full-blown
service orchestration process that supports sequence,
choice, and parallelism. The output of our algorithm
can be mapped directly into a number of service
orchestration languages such as OWL-S and BPEL. The
approach consists of two steps. First, semantic links
specifying data dependencies among the services are
derived and organized in a flexible network. Second,
based on a user request indicating the desired outcomes
from the composition, an executable composition is
constructed from the network that satisfies the
dependencies. The approach is unique in producing
complex compositions out of semantic links between
services in a flexible way. It also allows reusing
knowledge about semantic dependencies in the network to
generate new compositions through new requests and
modification of services at runtime. The approach has
been implemented in a prototype that outperforms
related composition prototypes in experiments.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Avila:2016:WTC,
author = "Bruno T. {\'A}vila and Rafael D. Lins",
title = "W-tree: a Compact External Memory Representation for
Webgraphs",
journal = j-TWEB,
volume = "10",
number = "1",
pages = "6:1--6:??",
month = feb,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2835181",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "World Wide Web applications need to use, constantly
update, and maintain large webgraphs for executing
several tasks, such as calculating the web impact
factor, finding hubs and authorities, performing link
analysis by webometrics tools, and ranking webpages by
web search engines. Such webgraphs need to use a large
amount of main memory, and, frequently, they do not
completely fit in, even if compressed. Therefore,
applications require the use of external memory. This
article presents a new compact representation for
webgraphs, called w-tree, which is designed
specifically for external memory. It supports the
execution of basic queries (e.g., full read, random
read, and batch random read), set-oriented queries
(e.g., superset, subset, equality, overlap, range,
inlink, and co-inlink), and some advanced queries, such
as edge reciprocal and hub and authority. Furthermore,
a new layout tree designed specifically for webgraphs
is also proposed, reducing the overall storage cost and
allowing the random read query to be performed with an
asymptotically faster runtime in the worst case. To
validate the advantages of the w-tree, a series of
experiments are performed to assess an implementation
of the w-tree comparing it to a compact main memory
representation. The results obtained show that w-tree
is competitive in compression time and rate and in
query time, which may execute several orders of
magnitude faster for set-oriented queries than its
competitors. The results provide empirical evidence
that it is feasible to use a compact external memory
representation for webgraphs in real applications,
contradicting the previous assumptions made by several
researchers.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wang:2016:STQ,
author = "Xinyu Wang and Jianke Zhu and Zibin Zheng and Wenjie
Song and Yuanhong Shen and Michael R. Lyu",
title = "A Spatial-Temporal {QoS} Prediction Approach for
Time-aware {Web} Service Recommendation",
journal = j-TWEB,
volume = "10",
number = "1",
pages = "7:1--7:??",
month = feb,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2801164",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Due to the popularity of service-oriented
architectures for various distributed systems, an
increasing number of Web services have been deployed
all over the world. Recently, Web service
recommendation became a hot research topic, one that
aims to accurately predict the quality of functional
satisfactory services for each end user. Generally, the
performance of Web service changes over time due to
variations of service status and network conditions.
Instead of employing the conventional temporal models,
we propose a novel spatial-temporal QoS prediction
approach for time-aware Web service recommendation,
where a sparse representation is employed to model QoS
variations. Specifically, we make a zero-mean Laplace
prior distribution assumption on the residuals of the
QoS prediction, which corresponds to a Lasso regression
problem. To effectively select the nearest neighbor for
the sparse representation of temporal QoS values, the
geo-location of web service is employed to reduce
searching range while improving prediction accuracy.
The extensive experimental results demonstrate that the
proposed approach outperforms state-of-art methods with
more than 10\% improvement on the accuracy of temporal
QoS prediction for time-aware Web service
recommendation.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Guo:2016:NEB,
author = "Guibing Guo and Jie Zhang and Neil Yorke-Smith",
title = "A Novel Evidence-Based {Bayesian} Similarity Measure
for Recommender Systems",
journal = j-TWEB,
volume = "10",
number = "2",
pages = "8:1--8:??",
month = may,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2856037",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "User-based collaborative filtering, a widely used
nearest neighbour-based recommendation technique,
predicts an item's rating by aggregating its ratings
from similar users. User similarity is traditionally
calculated by cosine similarity or the Pearson
correlation coefficient. However, both of these
measures consider only the direction of rating vectors,
and suffer from a range of drawbacks. To overcome these
issues, we propose a novel Bayesian similarity measure
based on the Dirichlet distribution, taking into
consideration both the direction and length of rating
vectors. We posit that not all the rating pairs should
be equally counted in order to accurately model user
correlation. Three different evidence factors are
designed to compute the weights of rating pairs.
Further, our principled method reduces correlation due
to chance and potential system bias. Experimental
results on six real-world datasets show that our method
achieves superior accuracy in comparison with
counterparts.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Frattolillo:2016:BFM,
author = "Franco Frattolillo",
title = "A Buyer-Friendly and Mediated Watermarking Protocol
for {Web} Context",
journal = j-TWEB,
volume = "10",
number = "2",
pages = "9:1--9:??",
month = may,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2856036",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Watermarking protocols are used in conjunction with
digital watermarking techniques to protect digital
copyright on the Internet. They define the schemes of
the web transactions by which buyers can purchase
protected digital content distributed by content
providers in a secure manner. Over the last few years,
significant examples of watermarking protocols have
been proposed in literature. However, a detailed
examination of such protocols has revealed a number of
problems that have to be addressed in order to make
them suited for current web context. Therefore, based
on the most relevant problems derived from literature,
this article identifies the main challenges posed by
the development of watermarking protocols for web
context and presents a watermarking protocol that
follows a new secure, buyer-centric and mediated design
approach able to meet such challenges.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wu:2016:QDQ,
author = "Wensheng Wu and Weiyi Meng and Weifeng Su and Guangyou
Zhou and Yao-Yi Chiang",
title = "{Q2P}: Discovering Query Templates via
Autocompletion",
journal = j-TWEB,
volume = "10",
number = "2",
pages = "10:1--10:??",
month = may,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2873061",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We present Q2P, a system that discovers query
templates from search engines via their query
autocompletion services. Q2P is distinct from the
existing works in that it does not rely on query logs
of search engines that are typically not readily
available. Q2P is also unique in that it uses a trie to
economically store queries sampled from a search engine
and employs a beam-search strategy that focuses the
expansion of the trie on its most promising nodes.
Furthermore, Q2P leverages the trie-based storage of
query sample to discover query templates using only two
passes over the trie. Q2P is a key part of our ongoing
project Deep2Q on a template-driven data integration on
the Deep Web, where the templates learned by Q2P are
used to guide the integration process in Deep2Q.
Experimental results on four major search engines
indicate that (1) Q2P sends only a moderate number of
queries (ranging from 597 to 1,135) to the engines,
while obtaining a significant number of completions per
query (ranging from 4.2 to 8.5 on the average); (2) a
significant number of templates (ranging from 8 to 32
when the minimum support for frequent templates is set
to 1\%) may be discovered from the samples.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Walk:2016:ADC,
author = "Simon Walk and Denis Helic and Florian Geigl and
Markus Strohmaier",
title = "Activity Dynamics in Collaboration Networks",
journal = j-TWEB,
volume = "10",
number = "2",
pages = "11:1--11:??",
month = may,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2873060",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Many online collaboration networks struggle to gain
user activity and become self-sustaining due to the
ramp-up problem or dwindling activity within the
system. Prominent examples include online encyclopedias
such as (Semantic) MediaWikis, Question and Answering
portals such as StackOverflow, and many others. Only a
small fraction of these systems manage to reach
self-sustaining activity, a level of activity that
prevents the system from reverting to a nonactive
state. In this article, we model and analyze activity
dynamics in synthetic and empirical collaboration
networks. Our approach is based on two opposing and
well-studied principles: (i) without incentives, users
tend to lose interest to contribute and thus, systems
become inactive, and (ii) people are susceptible to
actions taken by their peers (social or peer
influence). With the activity dynamics model that we
introduce in this article we can represent typical
situations of such collaboration networks. For example,
activity in a collaborative network, without external
impulses or investments, will vanish over time,
eventually rendering the system inactive. However, by
appropriately manipulating the activity dynamics and/or
the underlying collaboration networks, we can
jump-start a previously inactive system and advance it
toward an active state. To be able to do so, we first
describe our model and its underlying mechanisms. We
then provide illustrative examples of empirical
datasets and characterize the barrier that has to be
breached by a system before it can become
self-sustaining in terms of critical mass and activity
dynamics. Additionally, we expand on this empirical
illustration and introduce a new metric $p$ --- the
Activity Momentum --- to assess the activity robustness
of collaboration networks.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zheng:2016:PQA,
author = "Huiyuan Zheng and Jian Yang and Weiliang Zhao",
title = "Probabilistic {QoS} Aggregations for Service
Composition",
journal = j-TWEB,
volume = "10",
number = "2",
pages = "12:1--12:??",
month = may,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2876513",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In this article, we propose a comprehensive approach
for Quality of Service (QoS) calculation in service
composition. Differing from the existing work on QoS
aggregations that represent QoS as single values,
discrete values with frequencies, or standard
statistical distributions, the proposed approach has
the capability to handle any type of QoS probability
distribution. A set of formulae and algorithms are
developed to calculate the QoS of a composite service
according to four identified basic patterns as
sequential, parallel, conditional, and loop. We
demonstrate that the proposed QoS calculation method is
much more efficient than existing simulation methods.
It has a high scalability and builds a solid foundation
for real-time QoS analysis and prediction in service
composition. Experiment results are provided to show
the effectiveness and efficiency of the proposed
method.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Paul:2016:SBC,
author = "Michael J. Paul and Ryen W. White and Eric Horvitz",
title = "Search and Breast Cancer: On Episodic Shifts of
Attention over Life Histories of an Illness",
journal = j-TWEB,
volume = "10",
number = "2",
pages = "13:1--13:??",
month = may,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2893481",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We seek to understand the evolving needs of people who
are faced with a life-changing medical diagnosis based
on analyses of queries extracted from an anonymized
search query log. Focusing on breast cancer, we
manually tag a set of Web searchers as showing patterns
of search behavior consistent with someone grappling
with the screening, diagnosis, and treatment of breast
cancer. We build and apply probabilistic classifiers to
detect these searchers from multiple sessions and to
identify the timing of diagnosis using temporal and
statistical features. We explore the changes in
information seeking over time before and after an
inferred diagnosis of breast cancer by aligning
multiple searchers by the estimated time of diagnosis.
We employ the classifier to automatically identify
1,700 candidate searchers with an estimated 90\%
precision, and we predict the day of diagnosis within
15 days with an 88\% accuracy. We show that the
geographic and demographic attributes of searchers
identified with high probability are strongly
correlated with ground truth of reported incidence
rates. We then analyze the content of queries over time
for inferred cancer patients, using a detailed ontology
of cancer-related search terms. The analysis reveals
the rich temporal structure of the evolving queries of
people likely diagnosed with breast cancer. Finally, we
focus on subtypes of illness based on inferred stages
of cancer and show clinically relevant dynamics of
information seeking based on the dominant stage
expressed by searchers.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Doerfel:2016:WUA,
author = "Stephan Doerfel and Daniel Zoller and Philipp Singer
and Thomas Niebler and Andreas Hotho and Markus
Strohmaier",
title = "What Users Actually Do in a Social Tagging System: a
Study of User Behavior in {BibSonomy}",
journal = j-TWEB,
volume = "10",
number = "2",
pages = "14:1--14:??",
month = may,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2896821",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed May 25 17:02:04 MDT 2016",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Social tagging systems have established themselves as
an important part in today's Web and have attracted the
interest of our research community in a variety of
investigations. Henceforth, several aspects of social
tagging systems have been discussed and assumptions
have emerged on which our community builds their work.
Yet, testing such assumptions has been difficult due to
the absence of suitable usage data in the past. In this
work, we thoroughly investigate and evaluate four
aspects about tagging systems, covering social
interaction, retrieval of posted resources, the
importance of the three different types of entities,
users, resources, and tags, as well as connections
between these entities' popularity in posted and in
requested content. For that purpose, we examine live
server log data gathered from the real-world, public
social tagging system BibSonomy. Our empirical results
paint a mixed picture about the four aspects. Although
typical assumptions hold to a certain extent for some,
other aspects need to be reflected in a very critical
light. Our observations have implications for the
understanding of social tagging systems and the way
they are used on the Web. We make the dataset used in
this work available to other researchers.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Naini:2016:SEW,
author = "Kaweh Djafari Naini and Ismail Sengor Altingovde and
Wolf Siberski",
title = "Scalable and Efficient {Web} Search Result
Diversification",
journal = j-TWEB,
volume = "10",
number = "3",
pages = "15:1--15:??",
month = aug,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2907948",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:09 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "It has been shown that top-$k$ retrieval quality can
be considerably improved by taking not only relevance
but also diversity into account. However, currently
proposed diversification approaches have not put much
attention on practical usability in large-scale
settings, such as modern web search systems. In this
work, we make two contributions toward this goal.
First, we propose a combination of optimizations and
heuristics for an implicit diversification algorithm
based on the desirable facility placement principle,
and present two algorithms that achieve linear
complexity without compromising the retrieval
effectiveness. Instead of an exhaustive comparison of
documents, these algorithms first perform a clustering
phase and then exploit its outcome to compose the
diverse result set. Second, we describe and analyze two
variants for distributed diversification in a computing
cluster, for large-scale IR where the document
collection is too large to keep in one node. Our
contribution in this direction is pioneering, as there
exists no earlier work in the literature that
investigates the effectiveness and efficiency of
diversification on a distributed setup. Extensive
evaluations on a standard TREC framework demonstrate a
competitive retrieval quality of the proposed
optimizations to the baseline algorithm while reducing
the processing time by more than 80\% and up to 97\%,
and shed light on the efficiency and effectiveness
tradeoffs of diversification when applied on top of a
distributed architecture.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Furche:2016:PFW,
author = "Tim Furche and Giovanni Grasso and Michael Huemer and
Christian Schallhart and Michael Schrefl",
title = "{PeaCE-Ful} {Web} Event Extraction and Processing as
Bitemporal Mutable Events",
journal = j-TWEB,
volume = "10",
number = "3",
pages = "16:1--16:??",
month = aug,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2911989",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:09 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The web is the largest bulletin board of the world.
Events of all types, from flight arrivals to business
meetings, are announced on this board. Tracking and
reacting to such event announcements, however, is a
tedious manual task, only slightly alleviated by email
or similar notifications. Announcements are published
with human readers in mind, and updates or delayed
announcements are frequent. These characteristics have
hampered attempts at automatic tracking. P eaCE
provides the first integrated framework for event
processing on top of web event ads, consisting of event
extraction, complex event processing, and action
execution in response to these events. Given a schema
of the events to be tracked, the framework populates
this schema by extracting events from announcement
sources. This extraction is performed by little
programs called wrappers that produce the events
including updates and retractions. PeaCE then queries
these events to detect complex events, often combining
announcements from multiple sources. To deal with
updates and delayed announcements, PeaCE's schemas are
bitemporal, to distinguish between occurrence and
detection time. This allows complex event
specifications to track updates and to react upon
differences in occurrence and detection time. In case
of new, changing, or deleted events, PeaCE allows one
to execute actions, such as tweeting or sending out
email notifications. Actions are typically specified as
web interactions, for example, to fill and submit a
form with attributes of the triggering event. Our
evaluation shows that P eaCE's processing is dominated
by the time needed for accessing the web to extract
events and perform actions, allotting to 97.4\%. Thus,
PeaCE requires only 2.6\% overhead, and therefore, the
complex event processor scales well even with moderate
resources. We further show that simple and reasonable
restrictions on complex event specifications and the
timing of constituent events suffice to guarantee that
PeaCE only requires a constant buffer to process
arbitrarily many event announcements.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cranor:2016:LSE,
author = "Lorrie Faith Cranor and Pedro Giovanni Leon and Blase
Ur",
title = "A Large-Scale Evaluation of {U.S.} Financial
Institutions' Standardized Privacy Notices",
journal = j-TWEB,
volume = "10",
number = "3",
pages = "17:1--17:??",
month = aug,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2911988",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:09 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Financial institutions in the United States are
required by the Gramm-Leach-Bliley Act to provide
annual privacy notices. In 2009, eight federal agencies
jointly released a model privacy form for these
disclosures. While the use of this model privacy form
is not required, it has been widely adopted. We
automatically evaluated 6,191 U.S. financial
institutions' privacy notices posted on the World Wide
Web. We found large variance in stated practices, even
among institutions of the same type. While thousands of
financial institutions share personal information
without providing the opportunity for consumers to opt
out, some institutions' practices are more privacy
protective. Regression analyses show that large
institutions and those headquartered in the
northeastern region share consumers' personal
information at higher rates than all other
institutions. Furthermore, our analysis helped us
uncover institutions that do not let consumers limit
data sharing when legally required to do so, as well as
institutions making self-contradictory statements. We
discuss implications for privacy in the financial
industry, issues with the design and use of the model
privacy form on the World Wide Web, and future
directions for standardized privacy notice.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Srba:2016:CSC,
author = "Ivan Srba and Maria Bielikova",
title = "A Comprehensive Survey and Classification of
Approaches for Community Question Answering",
journal = j-TWEB,
volume = "10",
number = "3",
pages = "18:1--18:??",
month = aug,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2934687",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:09 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Community question-answering (CQA) systems, such as
Yahoo! Answers or Stack Overflow, belong to a prominent
group of successful and popular Web 2.0 applications,
which are used every day by millions of users to find
an answer on complex, subjective, or context-dependent
questions. In order to obtain answers effectively, CQA
systems should optimally harness collective
intelligence of the whole online community, which will
be impossible without appropriate collaboration support
provided by information technologies. Therefore, CQA
became an interesting and promising subject of research
in computer science and now we can gather the results
of 10 years of research. Nevertheless, in spite of the
increasing number of publications emerging each year,
so far the research on CQA systems has missed a
comprehensive state-of-the-art survey. We attempt to
fill this gap by a review of 265 articles published
between 2005 and 2014, which were selected from major
conferences and journals. According to this evaluation,
at first we propose a framework that defines
descriptive attributes of CQA approaches. Second, we
introduce a classification of all approaches with
respect to problems they are aimed to solve. The
classification is consequently employed in a review of
a significant number of representative approaches,
which are described by means of attributes from the
descriptive framework. As a part of the survey, we also
depict the current trends as well as highlight the
areas that require further attention from the research
community.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Hwang:2016:PPS,
author = "Seung-Won Hwang and Saehoon Kim and Yuxiong He and
Sameh Elnikety and Seungjin Choi",
title = "Prediction and Predictability for Search Query
Acceleration",
journal = j-TWEB,
volume = "10",
number = "3",
pages = "19:1--19:??",
month = aug,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2943784",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:09 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "A commercial web search engine shards its index among
many servers, and therefore the response time of a
search query is dominated by the slowest server that
processes the query. Prior approaches target improving
responsiveness by reducing the tail latency, or
high-percentile response time, of an individual search
server. They predict query execution time, and if a
query is predicted to be long-running, it runs in
parallel; otherwise, it runs sequentially. These
approaches are, however, not accurate enough for
reducing a high tail latency when responses are
aggregated from many servers because this requires each
server to reduce a substantially higher tail latency
(e.g., the 99.99th percentile), which we call extreme
tail latency. To address tighter requirements of
extreme tail latency, we propose a new design space for
the problem, subsuming existing work and also proposing
a new solution space. Existing work makes a prediction
using features available at indexing time and focuses
on optimizing prediction features for accelerating tail
queries. In contrast, we identify ``when to predict?''
as another key optimization question. This opens up a
new solution of delaying a prediction by a short
duration to allow many short-running queries to
complete without parallelization and, at the same time,
to allow the predictor to collect a set of dynamic
features using runtime information. This new question
expands a solution space in two meaningful ways. First,
we see a significant reduction of tail latency by
leveraging ``dynamic'' features collected at runtime
that estimate query execution time with higher
accuracy. Second, we can ask whether to override
prediction when the ``predictability'' is low. We show
that considering predictability accelerates the query
by achieving a higher recall. With this prediction, we
propose to accelerate the queries that are predicted to
be long-running. In our preliminary work, we focused on
parallelization as an acceleration scenario. We extend
to consider heterogeneous multicore hardware for
acceleration. This hardware combines processor cores
with different microarchitectures such as
energy-efficient little cores and high-performance big
cores, and accelerating web search using this hardware
has remained an open problem. We evaluate the proposed
prediction framework in two scenarios: (1) query
parallelization on a multicore processor and (2) query
scheduling on a heterogeneous processor. Our extensive
evaluation results show that, for both scenarios of
query acceleration using parallelization and
heterogeneous cores, the proposed framework is
effective in reducing the extreme tail latency compared
to a start-of-the-art predictor because of its higher
recall, and it improves server throughput by more than
70\% because of its improved precision.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Eraslan:2016:STA,
author = "Sukru Eraslan and Yeliz Yesilada and Simon Harper",
title = "Scanpath Trend Analysis on {Web} Pages: Clustering Eye
Tracking Scanpaths",
journal = j-TWEB,
volume = "10",
number = "4",
pages = "20:1--20:??",
month = dec,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2970818",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Eye tracking studies have widely been used in
improving the design and usability of web pages and in
the research of understanding how users navigate them.
However, there is limited research in clustering users'
eye movement sequences (i.e., scanpaths) on web pages
to identify a general direction they follow. Existing
research tends to be reductionist, which means that the
resulting path is so short that it is not useful.
Moreover, there is little work on correlating users'
scanpaths with visual elements of web pages and the
underlying source code, which means the result cannot
be used for further processing. In order to address
these limitations, we introduce a new concept in
clustering scanpaths called Scanpath Trend Analysis
(STA) that not only considers the visual elements
visited by all users, but also considers the visual
elements visited by the majority in any order. We
present an algorithm which automatically does this
trend analysis to identify a trending scanpath for
multiple web users in terms of visual elements of a web
page. In contrast to existing research, the STA
algorithm first analyzes the most visited visual
elements in given scanpaths, clusters the scanpaths by
arranging these visual elements based on their overall
positions in the individual scanpaths, and then
constructs a trending scanpath in terms of these visual
elements. This algorithm was experimentally evaluated
by an eye tracking study on six web pages for two
different kinds of tasks (12 cases in total). Our
experimental results show that the STA algorithm
generates a trending scanpath that addresses the
reductionist problem of existing work by preventing the
loss of commonly visited visual elements for all cases.
Based on the statistical tests, the STA algorithm also
generates a trending scanpath that is significantly
more similar to the inputted scanpaths compared to
other existing work in 10 out of 12 cases. In the
remaining cases, the STA algorithm still performs
significantly better than some other existing work.
This algorithm contributes to behavior analysis
research on the web that can be used for different
purposes: for example, re-engineering web pages guided
by the trending scanpath to improve users' experience
or guiding designers to improve their design.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Rafalak:2016:WCC,
author = "Maria Rafalak and Dominik Deja and Adam Wierzbicki and
Radoslaw Nielek and Michal Kakol",
title = "{Web} Content Classification Using Distributions of
Subjective Quality Evaluations",
journal = j-TWEB,
volume = "10",
number = "4",
pages = "21:1--21:??",
month = dec,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2994132",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Machine learning algorithms and recommender systems
trained on human ratings are widely in use today.
However, human ratings may be associated with a high
level of uncertainty and are subjective, influenced by
demographic or psychological factors. We propose a new
approach to the design of object classes from human
ratings: the use of entire distributions to construct
classes. By avoiding aggregation for class definition,
our approach loses no information and can deal with
highly volatile or conflicting ratings. The approach is
based the concept of the Earth Mover's Distance (EMD),
a measure of distance for distributions. We evaluate
the proposed approach based on four datasets obtained
from diverse Web content or movie quality evaluation
services or experiments. We show that clusters
discovered in these datasets using the EMD measure are
characterized by a consistent and simple
interpretation. Quality classes defined using entire
rating distributions can be fitted to clusters of
distributions in the four datasets using two
parameters, resulting in a good overall fit. We also
consider the impact of the composition of small samples
on the distributions that are the basis of our
classification approach. We show that using
distributions based on small samples of 10 evaluations
is still robust to several demographic and
psychological variables. This observation suggests that
the proposed approach can be used in practice for
quality evaluation, even for highly uncertain and
subjective ratings.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Guo:2016:FEE,
author = "Guangming Guo and Feida Zhu and Enhong Chen and Qi Liu
and Le Wu and Chu Guan",
title = "From Footprint to Evidence: an Exploratory Study of
Mining Social Data for Credit Scoring",
journal = j-TWEB,
volume = "10",
number = "4",
pages = "22:1--22:??",
month = dec,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/2996465",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "With the booming popularity of online social networks
like Twitter and Weibo, online user footprints are
accumulating rapidly on the social web. Simultaneously,
the question of how to leverage the large-scale
user-generated social media data for personal credit
scoring comes into the sight of both researchers and
practitioners. It has also become a topic of great
importance and growing interest in the P2P lending
industry. However, compared with traditional financial
data, heterogeneous social data presents both
opportunities and challenges for personal credit
scoring. In this article, we seek a deep understanding
of how to learn users' credit labels from social data
in a comprehensive and efficient way. Particularly, we
explore the social-data-based credit scoring problem
under the micro-blogging setting for its open, simple,
and real-time nature. To identify credit-related
evidence hidden in social data, we choose to conduct an
analytical and empirical study on a large-scale dataset
from Weibo, the largest and most popular tweet-style
website in China. Summarizing results from existing
credit scoring literature, we first propose three
social-data-based credit scoring principles as
guidelines for in-depth exploration. In addition, we
glean six credit-related insights arising from
empirical observations of the testbed dataset. Based on
the proposed principles and insights, we extract
prediction features mainly from three categories of
users' social data, including demographics, tweets, and
networks. To harness this broad range of features, we
put forward a two-tier stacking and boosting enhanced
ensemble learning framework. Quantitative investigation
of the extracted features shows that online social
media data does have good potential in discriminating
good credit users from bad. Furthermore, we perform
experiments on the real-world Weibo dataset consisting
of more than 7.3 million tweets and 200,000 users whose
credit labels are known through our third-party
partner. Experimental results show that (i) our
approach achieves a roughly 0.625 AUC value with all
the proposed social features as input, and (ii) our
learning algorithm can outperform traditional credit
scoring methods by as much as 17\% for
social-data-based personal credit scoring.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "22",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bahri:2016:CCO,
author = "Leila Bahri and Barbara Carminati and Elena Ferrari",
title = "{COIP}-Continuous, Operable, Impartial, and
Privacy-Aware Identity Validity Estimation for {OSN}
Profiles",
journal = j-TWEB,
volume = "10",
number = "4",
pages = "23:1--23:??",
month = dec,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/3014338",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Identity validation of Online Social Networks' (OSNs')
peers is a critical concern to the insurance of safe
and secure online socializing environments. Starting
from the vision of empowering users to determine the
validity of OSN identities, we suggest a framework to
estimate the trustworthiness of online social profiles
based only on the information they contain. Our
framework is based on learning identity correlations
between profile attributes in an OSN community and on
collecting ratings from OSN community members to
evaluate the trustworthiness of target profiles. Our
system guarantees utility, user anonymity, impartiality
in rating, and operability within the dynamics and
continuous evolution of OSNs. In this article, we
detail the system design, and we prove its correctness
against these claimed quality properties. Moreover, we
test its effectiveness, feasibility, and efficiency
through experimentation on real-world datasets from
Facebook and Google+, in addition to using the Adults
UCI dataset.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "23",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Das:2016:MAA,
author = "Sanmay Das and Allen Lavoie and Malik Magdon-Ismail",
title = "Manipulation among the Arbiters of Collective
Intelligence: How {Wikipedia} Administrators Mold
Public Opinion",
journal = j-TWEB,
volume = "10",
number = "4",
pages = "24:1--24:??",
month = dec,
year = "2016",
CODEN = "????",
DOI = "https://doi.org/10.1145/3001937",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Our reliance on networked, collectively built
information is a vulnerability when the quality or
reliability of this information is poor. Wikipedia, one
such collectively built information source, is often
our first stop for information on all kinds of topics;
its quality has stood up to many tests, and it prides
itself on having a ``neutral point of view.''
Enforcement of neutrality is in the hands of
comparatively few, powerful administrators. In this
article, we document that a surprisingly large number
of editors change their behavior and begin focusing
more on a particular controversial topic once they are
promoted to administrator status. The conscious and
unconscious biases of these few, but powerful,
administrators may be shaping the information on many
of the most sensitive topics on Wikipedia; some may
even be explicitly infiltrating the ranks of
administrators in order to promote their own points of
view. In addition, we ask whether administrators who
change their behavior in this suspicious manner can be
identified in advance. Neither prior history nor vote
counts during an administrator's election are useful in
doing so, but we find that an alternative measure,
which gives more weight to influential voters, can
successfully reject these suspicious candidates. This
second result has important implications for how we
harness collective intelligence: even if wisdom exists
in a collective opinion (like a vote), that signal can
be lost unless we carefully distinguish the true expert
voter from the noisy or manipulative voter.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "24",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Mukherjee:2017:ISV,
author = "Partha Mukherjee and Bernard J. Jansen",
title = "Information Sharing by Viewers Via Second Screens for
In-Real-Life Events",
journal = j-TWEB,
volume = "11",
number = "1",
pages = "1:1--1:??",
month = mar,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3009970",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The use of second screen devices with social media
facilitates conversational interaction concerning
broadcast media events, creating what we refer to as
the social soundtrack. In this research, we evaluate
the change of the Super Bowl XLIX social soundtrack
across three social media platforms on the topical
categories of commercials, music, and game at three
game phases ( Pre, During, and Post ). We perform
statistical analysis on more than 3M, 800K, and 50K
posts from Twitter, Instagram, and Tumblr,
respectively. Findings show that the volume of posts in
the During phase is fewer compared to Pre and Post
phases; however, the hourly mean in the During phase is
considerably higher than it is in the other two phases.
We identify the predominant phase and category of
interaction across all three social media sites. We
also determine the significance of change in absolute
scale across the Super Bowl categories (commercials,
music, game) and in both absolute and relative scales
across Super Bowl phases ( Pre, During, Post ) for the
three social network platforms (Twitter, Tumblr,
Instagram). Results show that significant
phase-category relationships exist for all three social
networks. The results identify the During phase as the
predominant one for all three categories on all social
media sites with respect to the absolute volume of
conversations in a continuous scale. From the relative
volume perspective, the During phase is highest for the
music category for most social networks. For the
commercials and game categories, however, the Post
phase is higher than the During phase for Twitter and
Instagram, respectively. Regarding category
identification, the game category is the highest for
Twitter and Instagram but not for Tumblr, which has
dominant peaks for music and/or commercials in all
three phases. It is apparent that different social
media platforms offer various phase and category
affordances. These results are important in identifying
the influence that second screen technology has on
information sharing across different social media
platforms and indicates that the viewer role is
transitioning from passive to more active.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Squicciarini:2017:TAO,
author = "Anna Squicciarini and Cornelia Caragea and Rahul
Balakavi",
title = "Toward Automated Online Photo Privacy",
journal = j-TWEB,
volume = "11",
number = "1",
pages = "2:1--2:??",
month = mar,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/2983644",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Online photo sharing is an increasingly popular
activity for Internet users. More and more users are
now constantly sharing their images in various social
media, from social networking sites to online
communities, blogs, and content sharing sites. In this
article, we present an extensive study exploring
privacy and sharing needs of users' uploaded images. We
develop learning models to estimate adequate privacy
settings for newly uploaded images, based on carefully
selected image-specific features. Our study
investigates both visual and textual features of images
for privacy classification. We consider both basic
image-specific features, commonly used for image
processing, as well as more sophisticated and abstract
visual features. Additionally, we include a visual
representation of the sentiment evoked by images. To
our knowledge, sentiment has never been used in the
context of image classification for privacy purposes.
We identify the smallest set of features, that by
themselves or combined together with others, can
perform well in properly predicting the degree of
sensitivity of users' images. We consider both the case
of binary privacy settings (i.e., public, private), as
well as the case of more complex privacy options,
characterized by multiple sharing options. Our results
show that with few carefully selected features, one may
achieve high accuracy, especially when high-quality
tags are available.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Kang:2017:EMA,
author = "Jeon-Hyung Kang and Kristina Lerman",
title = "Effort Mediates Access to Information in Online Social
Networks",
journal = j-TWEB,
volume = "11",
number = "1",
pages = "3:1--3:??",
month = mar,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/2990506",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Individuals' access to information in a social network
depends on how it is distributed and where in the
network individuals position themselves. In addition,
individuals vary in how much effort they invest in
managing their social connections. Using data from a
social media site, we study how the interplay between
effort and network position affects social media users'
access to diverse and novel information. Previous
studies of the role of networks in information access
were limited in their ability to measure the diversity
of information. We address this problem by learning the
topics of interest to social media users from the
messages they share online with followers. We use the
learned topics to measure the diversity of information
users receive from the people they follow online. We
confirm that users in structurally diverse network
positions, which bridge otherwise disconnected regions
of the follower network, tend to be exposed to more
diverse and novel information. We also show that users
who invest more effort in their activity on the site
are not only located in more structurally diverse
positions within the network than the less engaged
users but also receive more novel and diverse
information when in similar network positions. These
findings indicate that the relationship between network
structure and access to information in networks is more
nuanced than previously thought.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Seneviratne:2017:SMA,
author = "Suranga Seneviratne and Aruna Seneviratne and Mohamed
Ali Kaafar and Anirban Mahanti and Prasant Mohapatra",
title = "Spam Mobile Apps: Characteristics, Detection, and in
the Wild Analysis",
journal = j-TWEB,
volume = "11",
number = "1",
pages = "4:1--4:??",
month = mar,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3007901",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The increased popularity of smartphones has attracted
a large number of developers to offer various
applications for the different smartphone platforms via
the respective app markets. One consequence of this
popularity is that the app markets are also becoming
populated with spam apps. These spam apps reduce the
users' quality of experience and increase the workload
of app market operators to identify these apps and
remove them. Spam apps can come in many forms such as
apps not having a specific functionality, those having
unrelated app descriptions or unrelated keywords, or
similar apps being made available several times and
across diverse categories. Market operators maintain
antispam policies and apps are removed through
continuous monitoring. Through a systematic crawl of a
popular app market and by identifying apps that were
removed over a period of time, we propose a method to
detect spam apps solely using app metadata available at
the time of publication. We first propose a methodology
to manually label a sample of removed apps, according
to a set of checkpoint heuristics that reveal the
reasons behind removal. This analysis suggests that
approximately 35\% of the apps being removed are very
likely to be spam apps. We then map the identified
heuristics to several quantifiable features and show
how distinguishing these features are for spam apps. We
build an Adaptive Boost classifier for early
identification of spam apps using only the metadata of
the apps. Our classifier achieves an accuracy of over
95\% with precision varying between 85\% and 95\% and
recall varying between 38\% and 98\%. We further show
that a limited number of features, in the range of
10--30, generated from app metadata is sufficient to
achieve a satisfactory level of performance. On a set
of 180,627 apps that were present at the app market
during our crawl, our classifier predicts 2.7\% of the
apps as potential spam. Finally, we perform additional
manual verification and show that human reviewers agree
with 82\% of our classifier predictions.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Uribe:2017:UWP,
author = "Silvia Uribe and Federico {\'A}lvarez and Jos{\'e}
Manuel Men{\'e}ndez",
title = "User's {Web} Page Aesthetics Opinion: a Matter of
Low-Level Image Descriptors Based on {MPEG-7}",
journal = j-TWEB,
volume = "11",
number = "1",
pages = "5:1--5:??",
month = mar,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3019595",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Analyzing a user's first impression of a Web site is
essential for interface designers, as it is tightly
related to their overall opinion of a site. In fact,
this early evaluation affects user navigation behavior.
Perceived usability and user interest (e.g., revisiting
and recommending the site) are parameters influenced by
first opinions. Thus, predicting the latter when
creating a Web site is vital to ensure users'
acceptance. In this regard, Web aesthetics is one of
the most influential factors in this early perception.
We propose the use of low-level image parameters for
modeling Web aesthetics in an objective manner, which
is an innovative research field. Our model, obtained by
applying a stepwise multiple regression algorithm,
infers a user's first impression by analyzing three
different visual characteristics of Web site
screenshots-texture, luminance, and color-which are
directly derived from MPEG-7 descriptors. The results
obtained over three wide Web site datasets (composed by
415, 42, and 6 Web sites, respectively) reveal a high
correlation between low-level parameters and the users'
evaluation, thus allowing a more precise and objective
prediction of users' opinion than previous models that
are based on other image characteristics with fewer
predictors. Therefore, our model is meant to support a
rapid assessment of Web sites in early stages of the
design process to maximize the likelihood of the users'
final approval.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Parra-Arnau:2017:MBT,
author = "Javier Parra-Arnau and Jagdish Prasad Achara and
Claude Castelluccia",
title = "{MyAdChoices}: Bringing Transparency and Control to
Online Advertising",
journal = j-TWEB,
volume = "11",
number = "1",
pages = "7:1--7:??",
month = mar,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/2996466",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 3 11:10:10 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The intrusiveness and the increasing invasiveness of
online advertising have, in the last few years, raised
serious concerns regarding user privacy and Web
usability. As a reaction to these concerns, we have
witnessed the emergence of a myriad of ad-blocking and
antitracking tools, whose aim is to return control to
users over advertising. The problem with these
technologies, however, is that they are extremely
limited and radical in their approach: users can only
choose either to block or allow all ads. With around
200 million people regularly using these tools, the
economic model of the Web-in which users get content
free in return for allowing advertisers to show them
ads-is at serious peril. In this article, we propose a
smart Web technology that aims at bringing transparency
to online advertising, so that users can make an
informed and equitable decision regarding ad blocking.
The proposed technology is implemented as a Web-browser
extension and enables users to exert fine-grained
control over advertising, thus providing them with
certain guarantees in terms of privacy and browsing
experience, while preserving the Internet economic
model. Experimental results in a real environment
demonstrate the suitability and feasibility of our
approach, and provide preliminary findings on
behavioral targeting from real user browsing
profiles.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wang:2017:VMC,
author = "Tianyi Wang and Gang Wang and Bolun Wang and Divya
Sambasivan and Zengbin Zhang and Xing Li and Haitao
Zheng and Ben Y. Zhao",
title = "Value and Misinformation in Collaborative Investing
Platforms",
journal = j-TWEB,
volume = "11",
number = "2",
pages = "8:1--8:??",
month = may,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3027487",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:38 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "It is often difficult to separate the highly capable
``experts'' from the average worker in crowdsourced
systems. This is especially true for challenge
application domains that require extensive domain
knowledge. The problem of stock analysis is one such
domain, where even the highly paid, well-educated
domain experts are prone to make mistakes. As an
extremely challenging problem space, the ``wisdom of
the crowds'' property that many crowdsourced
applications rely on may not hold. In this article, we
study the problem of evaluating and identifying experts
in the context of SeekingAlpha and StockTwits, two
crowdsourced investment services that have recently
begun to encroach on a space dominated for decades by
large investment banks. We seek to understand the
quality and impact of content on collaborative
investment platforms, by empirically analyzing complete
datasets of SeekingAlpha articles (9 years) and
StockTwits messages (4 years). We develop sentiment
analysis tools and correlate contributed content to the
historical performance of relevant stocks. While
SeekingAlpha articles and StockTwits messages provide
minimal correlation to stock performance in aggregate,
a subset of experts contribute more valuable
(predictive) content. We show that these authors can be
easily identified by user interactions, and investments
based on their analysis significantly outperform
broader markets. This effectively shows that even in
challenging application domains, there is a secondary
or indirect wisdom of the crowds. Finally, we conduct a
user survey that sheds light on users' views of
SeekingAlpha content and stock manipulation. We also
devote efforts to identify potential manipulation of
stocks by detecting authors controlling multiple
identities.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Drutsa:2017:PUE,
author = "Alexey Drutsa and Gleb Gusev and Pavel Serdyukov",
title = "Periodicity in User Engagement with a Search Engine
and Its Application to Online Controlled Experiments",
journal = j-TWEB,
volume = "11",
number = "2",
pages = "9:1--9:??",
month = may,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/2856822",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:38 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Nowadays, billions of people use the Web in connection
with their daily needs. A significant part of these
needs are constituted by search tasks that are usually
addressed by search engines. Thus, daily search needs
result in regular user engagement with a search engine.
User engagement with web services was studied in
various aspects, but there appears to be little work
devoted to its regularity and periodicity. In this
article, we study periodicity of user engagement with a
popular search engine through applying spectrum
analysis to temporal sequences of different engagement
metrics. First, we found periodicity patterns of user
engagement and revealed classes of users whose
periodicity patterns do not change over a long period
of time. In addition, we give an exhaustive analysis of
the stability and quality of identified clusters.
Second, we used the spectrum series as key metrics to
evaluate search quality. We found that the novel
periodicity metrics outperform the state-of-the-art
quality metrics both in terms of significance level ( p
-value) and sensitivity to a large set of larges-scale
A/B experiments conducted on real search engine
users.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Rahman:2017:AAC,
author = "M. Rezaur Rahman and Jinyoung Han and Yong Jae Lee and
Chen-Nee Chuah",
title = "Analyzing the Adoption and Cascading Process of
{OSN}-Based Gifting Applications: an Empirical Study",
journal = j-TWEB,
volume = "11",
number = "2",
pages = "10:1--10:??",
month = may,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3023871",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:38 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "To achieve growth in the user base of online social
networks--(OSN) based applications, word-of-mouth
diffusion mechanisms, such as user-to-user invitations,
are widely used. This article characterizes the
adoption and cascading process of OSN-based
applications that grow via user invitations. We analyze
a detailed large-scale dataset of a popular Facebook
gifting application, iHeart, that contains more than 2
billion entries of user activities generated by 190
million users during a span of 64 weeks. We investigate
(1) how users invite their friends to an OSN-based
application, (2) how application adoption of an
individual user can be predicted, (3) what factors
drive the cascading process of application adoptions,
and (4) what are the good predictors of the ultimate
cascade sizes. We find that sending or receiving a
large number of invitations does not necessarily help
to recruit new users to iHeart. We also find that the
average success ratio of inviters is the most important
feature in predicting an adoption of an individual
user, which indicates that the effectiveness of
inviters has strong predictive power with respect to
application adoption. Based on the lessons learned from
our analyses, we build and evaluate learning-based
models to predict whether a user will adopt iHeart. Our
proposed model that utilizes additional activity
information of individual users from other similar
types of gifting applications can achieve high
precision (83\%) in predicting adoptions in the target
application (i.e., iHeart). We next identify a set of
distinctive features that are good predictors of the
growth of the application adoptions in terms of final
population size. We finally propose a prediction model
to infer whether a cascade of application adoption will
continue to grow in the future based on observing the
initial adoption process. Results show that our
proposed model can achieve high precision (over 80\%)
in predicting large cascades of application adoptions.
We believe our work can give an important implication
in resource allocation of OSN-based product
stakeholders, for example, via targeted marketing.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Matsubara:2017:NDI,
author = "Yasuko Matsubara and Yasushi Sakurai and B. Aditya
Prakash and Lei Li and Christos Faloutsos",
title = "Nonlinear Dynamics of Information Diffusion in Social
Networks",
journal = j-TWEB,
volume = "11",
number = "2",
pages = "11:1--11:??",
month = may,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3057741",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:38 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/string-matching.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The recent explosion in the adoption of search engines
and new media such as blogs and Twitter have
facilitated the faster propagation of news and rumors.
How quickly does a piece of news spread over these
media? How does its popularity diminish over time? Does
the rising and falling pattern follow a simple
universal law? In this article, we propose SpikeM, a
concise yet flexible analytical model of the rise and
fall patterns of information diffusion. Our model has
the following advantages. First, unification power: it
explains earlier empirical observations and generalizes
theoretical models including the SI and SIR models. We
provide the threshold of the take-off versus die-out
conditions for SpikeM and discuss the generality of our
model by applying it to an arbitrary graph topology.
Second, practicality: it matches the observed behavior
of diverse sets of real data. Third, parsimony: it
requires only a handful of parameters. Fourth,
usefulness: it makes it possible to perform analytic
tasks such as forecasting, spotting anomalies, and
interpretation by reverse engineering the system
parameters of interest (quality of news, number of
interested bloggers, etc.). We also introduce an
efficient and effective algorithm for the real-time
monitoring of information diffusion, namely
SpikeStream, which identifies multiple diffusion
patterns in a large collection of online event streams.
Extensive experiments on real datasets demonstrate that
SpikeM accurately and succinctly describes all patterns
of the rise and fall spikes in social networks.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Rojas-Galeano:2017:OOO,
author = "Sergio Rojas-Galeano",
title = "On Obstructing Obscenity Obfuscation",
journal = j-TWEB,
volume = "11",
number = "2",
pages = "12:1--12:??",
month = may,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3032963",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:38 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Obscenity (the use of rude words or offensive
expressions) has spread from informal verbal
conversations to digital media, becoming increasingly
common on user-generated comments found in Web forums,
newspaper user boards, social networks, blogs, and
media-sharing sites. The basic obscenity-blocking
mechanism is based on verbatim comparisons against a
blacklist of banned vocabulary; however, creative users
circumvent these filters by obfuscating obscenity with
symbol substitutions or bogus segmentations that still
visually preserve the original semantics, such as
writing shit as {\em \$h`!t\/} or {\em s.h.i.t\/} or
even worse mixing them as {\em \$.h....`!.t\/}. The
number of potential obfuscated variants is
combinatorial, yielding the verbatim filter
impractical. Here we describe a method intended to
obstruct this anomaly inspired by sequence alignment
algorithms used in genomics, coupled with a tailor-made
edit penalty function. The method only requires to set
up the vocabulary of plain obscenities; no further
training is needed. Its complexity on screening a
single obscenity is linear, both in runtime and memory,
on the length of the user-generated text. We validated
the method on three different experiments. The first
one involves a new dataset that is also introduced in
this article; it consists of a set of manually
annotated real-life comments in Spanish, gathered from
the news user boards of an online newspaper, containing
this type of obfuscation. The second one is a publicly
available dataset of comments in Portuguese from a
sports Web site. In these experiments, at the obscenity
level, we observed recall rates greater than 90\%,
whereas precision rates varied between 75\% and 95\%,
depending on their sequence length (shorter lengths
yielded a higher number of false alarms). On the other
hand, at the comment level, we report recall of 86\%,
precision of 91\%, and specificity of 98\%. The last
experiment revealed that the method is more effective
in matching this type of obfuscation compared to the
classical Levenshtein edit distance. We conclude
discussing the prospects of the method to help
enforcing moderation rules of obscenity expressions or
as a preprocessing mechanism for sequence cleaning
and/or feature extraction in more sophisticated text
categorization techniques.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Xu:2017:EIE,
author = "Haitao Xu and Daiping Liu and Haining Wang and Angelos
Stavrou",
title = "An Empirical Investigation of
Ecommerce-Reputation-Escalation-as-a-Service",
journal = j-TWEB,
volume = "11",
number = "2",
pages = "13:1--13:??",
month = may,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/2983646",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:38 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In online markets, a store's reputation is closely
tied to its profitability. Sellers' desire to quickly
achieve a high reputation has fueled a profitable
underground business that operates as a specialized
crowdsourcing marketplace and accumulates wealth by
allowing online sellers to harness human laborers to
conduct fake transactions to improve their stores'
reputations. We term such an underground market a
seller-reputation-escalation (SRE) market. In this
article, we investigate the impact of the SRE service
on reputation escalation by performing in-depth
measurements of the prevalence of the SRE service, the
business model and market size of SRE markets, and the
characteristics of sellers and offered laborers. To
this end, we have infiltrated five SRE markets and
studied their operations using daily data collection
over a continuous period of 2 months. We identified
more than 11,000 online sellers posting at least
219,165 fake-purchase tasks on the five SRE markets.
These transactions earned at least \$46,438 in revenue
for the five SRE markets, and the total value of
merchandise involved exceeded \$3,452,530. Our study
demonstrates that online sellers using the SRE service
can increase their stores' reputations at least 10
times faster than legitimate ones while about 25\% of
them were visibly penalized. Even worse, we found a
much stealthier and more hazardous service that can,
within a single day, boost a seller's reputation by
such a degree that would require a legitimate seller at
least a year to accomplish. Armed with our analysis of
the operational characteristics of the underground
economy, we offer some insights into potential
mitigation strategies. Finally, we revisit the SRE
ecosystem 1 year later to evaluate the latest dynamism
of the SRE markets, especially the statuses of the
online stores once identified to launch
fake-transaction campaigns on the SRE markets. We
observe that the SRE markets are not as active as they
were 1 year ago and about 17\% of the involved online
stores become inaccessible likely because they have
been forcibly shut down by the corresponding E-commerce
marketplace for conducting fake transactions.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Singer:2017:BMC,
author = "Philipp Singer and Denis Helic and Andreas Hotho and
Markus Strohmaier",
title = "A {Bayesian} Method for Comparing Hypotheses About
Human Trails",
journal = j-TWEB,
volume = "11",
number = "3",
pages = "14:1--14:??",
month = jul,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3054950",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:39 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "When users interact with the Web today, they leave
sequential digital trails on a massive scale. Examples
of such human trails include Web navigation, sequences
of online restaurant reviews, or online music play
lists. Understanding the factors that drive the
production of these trails can be useful, for example,
for improving underlying network structures, predicting
user clicks, or enhancing recommendations. In this
work, we present a method called HypTrails for
comparing a set of hypotheses about human trails on the
Web, where hypotheses represent beliefs about
transitions between states. Our method utilizes Markov
chain models with Bayesian inference. The main idea is
to incorporate hypotheses as informative Dirichlet
priors and to calculate the evidence of the data under
them. For eliciting Dirichlet priors from hypotheses,
we present an adaption of the so-called (trial)
roulette method, and to compare the relative
plausibility of hypotheses, we employ Bayes factors. We
demonstrate the general mechanics and applicability of
HypTrails by performing experiments with (i) synthetic
trails for which we control the mechanisms that have
produced them and (ii) empirical trails stemming from
different domains including Web site navigation,
business reviews, and online music played. Our work
expands the repertoire of methods available for
studying human trails.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Vahedian:2017:MRH,
author = "Fatemeh Vahedian and Robin Burke and Bamshad
Mobasher",
title = "Multirelational Recommendation in Heterogeneous
Networks",
journal = j-TWEB,
volume = "11",
number = "3",
pages = "15:1--15:??",
month = jul,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3054952",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:39 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Recommender systems are key components in
information-seeking contexts where personalization is
sought. However, the dominant framework for
recommendation is essentially two dimensional, with the
interaction between users and items characterized by a
single relation. In many cases, such as social
networks, users and items are joined in a complex web
of relations, not readily reduced to a single value.
Recent multirelational approaches to recommendation
focus on the direct, proximal relations in which users
and items may participate. Our approach uses the
framework of complex heterogeneous networks to
represent such recommendation problems. We propose the
weighted hybrid of low-dimensional recommenders
(WHyLDR) recommendation model, which uses extended
relations, represented as constrained network paths, to
effectively augment direct relations. This model
incorporates influences from both distant and proximal
connections in the network. The WHyLDR approach raises
the problem of the unconstrained proliferation of
components, built from ever-extended network paths. We
show that although component utility is not strictly
monotonic with path length, a measure based on
information gain can effectively prune and optimize
such hybrids.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Sariyuce:2017:NDI,
author = "Ahmet Erdem Sariy{\"u}ce and C. Seshadhri and Ali
Pinar and {\"U}mit V. {\c{C}}ataly{\"u}rek",
title = "Nucleus Decompositions for Identifying Hierarchy of
Dense Subgraphs",
journal = j-TWEB,
volume = "11",
number = "3",
pages = "16:1--16:??",
month = jul,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3057742",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:39 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Finding dense substructures in a graph is a
fundamental graph mining operation, with applications
in bioinformatics, social networks, and visualization
to name a few. Yet most standard formulations of this
problem (like clique, quasi-clique, densest at-least- k
subgraph) are NP-hard. Furthermore, the goal is rarely
to find the ``true optimum'' but to identify many (if
not all) dense substructures, understand their
distribution in the graph, and ideally determine
relationships among them. Current dense subgraph
finding algorithms usually optimize some objective and
only find a few such subgraphs without providing any
structural relations. We define the nucleus
decomposition of a graph, which represents the graph as
a forest of nuclei. Each nucleus is a subgraph where
smaller cliques are present in many larger cliques. The
forest of nuclei is a hierarchy by containment, where
the edge density increases as we proceed towards leaf
nuclei. Sibling nuclei can have limited intersections,
which enables discovering overlapping dense
subgraphs. With the right parameters, the nucleus
decomposition generalizes the classic notions of
$k$-core and $k$-truss decompositions. We present
practical algorithms for nucleus decompositions and
empirically evaluate their behavior in a variety of
real graphs. The tree of nuclei consistently gives a
global, hierarchical snapshot of dense substructures
and outputs dense subgraphs of comparable quality with
the state-of-the-art solutions that are dense and have
non-trivial sizes. Our algorithms can process
real-world graphs with tens of millions of edges in
less than an hour. We demonstrate how proposed
algorithms can be utilized on a citation network. Our
analysis showed that dense units identified by our
algorithms correspond to coherent articles on a
specific area. Our experiments also show that we can
identify dense structures that are lost within larger
structures by other methods and find further finer
grain structure within dense groups.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Kanza:2017:LBD,
author = "Yaron Kanza and Elad Kravi and Eliyahu Safra and
Yehoshua Sagiv",
title = "Location-Based Distance Measures for Geosocial
Similarity",
journal = j-TWEB,
volume = "11",
number = "3",
pages = "17:1--17:??",
month = jul,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3054951",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:39 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This article investigates the problem of geosocial
similarity among users of online social networks, based
on the locations of their activities (e.g., posting
messages or photographs). Finding pairs of geosocially
similar users or detecting that two sets of locations
(of activities) belong to the same user has important
applications in privacy protection, recommendation
systems, urban planning, and public health, among
others. It is explained and shown empirically that
common distance measures between sets of locations are
inadequate for determining geosocial similarity. Two
novel distance measures between sets of locations are
introduced. One is the mutually nearest distance that
is based on computing a matching between two sets. The
second measure uses a quad-tree index. It is highly
scalable but incurs the overhead of creating and
maintaining the index. Algorithms with optimization
techniques are developed for computing the two distance
measures and also for finding the $k$-most-similar
users of a given one. Extensive experiments, using
geotagged messages from Twitter, show that the new
distance measures are both more accurate and more
efficient than existing ones.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Panagopoulos:2017:MER,
author = "A. Panagopoulos and E. Koutrouli and A. Tsalgatidou",
title = "Modeling and Evaluating a Robust Feedback-Based
Reputation System for E-Commerce Platforms",
journal = j-TWEB,
volume = "11",
number = "3",
pages = "18:1--18:??",
month = jul,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3057265",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:39 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Despite the steady growth of e-commerce communities in
the past two decades, little has changed in the way
these communities manage reputation for building trust
and for protecting their member's financial interests
against fraud. As these communities mature and the
defects of their reputation systems are revealed,
further potential for deception against their members
is created, that pushes the need for novel reputation
mechanisms. Although a high volume of research works
has explored the concepts of reputation and trust in
e-communities, most of the proposed reputation systems
target decentralized e-communities, focusing on issues
related with the decentralized reputation management;
they have not thus been integrated in e-commerce
platforms. This work's objective is to provide an
attackresilient feedback-based reputation system for
modern e-commerce platforms, while minimizing the
incurred financial burden of potent security schemes.
Initially, we discuss a series of attacks and issues in
reputation systems and study the different approaches
of these problems from related works, while also
considering the structural properties, defense
mechanisms and policies of existing platforms. Then we
present our proposition for a robust reputation system
which consists of a novel reputation metric and attack
prevention mechanisms. Finally, we describe the
simulation framework and tool that we have implemented
for thoroughly testing and evaluating the metric's
resilience against attacks and present the evaluation
experiments and their results. We consider the
presented simulation framework as the second
contribution of our article, aiming at facilitating the
simulation and elaborate evaluation of reputation
systems which specifically target e-commerce platforms
by thoroughly presenting it, exhibiting its usage and
making it available to the research community.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bianchini:2017:WMD,
author = "Devis Bianchini and Valeria {De Antonellis} and
Michele Melchiori",
title = "{WISeR}: a Multi-Dimensional Framework for Searching
and Ranking {Web APIs}",
journal = j-TWEB,
volume = "11",
number = "3",
pages = "19:1--19:??",
month = jul,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3061710",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 13 14:33:39 MDT 2017",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Mashups are agile applications that aggregate RESTful
services, developed by third parties, whose functions
are exposed as Web Application Program Interfaces
(APIs) within public repositories. From mashups
developers' viewpoint, Web API search may benefit from
selection criteria that combine several dimensions used
to describe the APIs, such as categories, tags, and
technical features (e.g., protocols and data formats).
Nevertheless, other dimensions might be fruitfully
exploited to support Web API search. Among them, past
API usage experiences by other developers may be used
to suggest the right APIs for a target application.
Past experiences might emerge from the co-occurrence of
Web APIs in the same mashups. Ratings assigned by
developers after using the Web APIs to create their own
mashups or after using mashups developed by others can
be considered as well. This article aims to advance the
current state of the art for Web API search and ranking
from mashups developers' point of view, by addressing
two key issues: multi-dimensional modeling and
multi-dimensional framework for selection. The model
for Web API characterization embraces multiple
descriptive dimensions, by considering several public
repositories, that focus on different and only
partially overlapping dimensions. The proposed Web API
selection framework, called WISeR (Web apI Search and
Ranking), is based on functions devoted to developers
to exploit the multi-dimensional descriptions, in order
to enhance the identification of candidate Web APIs to
be proposed, according to the given requirements.
Furthermore, WISeR adapts to changes that occur during
the Web API selection and mashup development, by
revising the dimensional attributes in order to conform
to developers' preferences and constraints. We also
present an experimental evaluation of the framework.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Rocha:2017:LPL,
author = "Andr{\'e} Rocha and C{\'a}ssio Prazeres",
title = "{LDoW--PaN}: Linked Data on the {Web}-Presentation and
Navigation",
journal = j-TWEB,
volume = "11",
number = "4",
pages = "20:1--20:??",
month = sep,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/2983643",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 15 08:22:45 MST 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This work aimed to propose LDoW-PaN, a Linked Data
presentation and navigation model focused on the
average user. The LDoW-PaN model is an extension of the
Dexter Hypertext Reference Model. Through the LDoW-PaN
model, ordinary people-who have no experience with
technologies that involve the Linked Data
environment-can interact with the Web of Data (RDF)
more closely related to how they interact with the Web
of Documents (HTML). To evaluate the proposal, some
tools were developed, including the following: (i) a
Web Service, which implements the lower-level layers of
the LDoW-PaN model; (ii) a client-side script library,
which implements the presentation and navigation layer;
and (iii) a browser extension, which uses these tools
to provide Linked Data presentation and navigation to
users browsing the Web. The browser extension was
developed using user interface approaches that are well
known, well accepted, and evaluated by the Web research
community, such as faceted navigation and presentation
through tooltips. Therefore, the prototype evaluation
included: usability evaluation through two classical
techniques; computational complexity measures; and an
analysis of the performance of the operations provided
by the proposed model.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wang:2017:CUB,
author = "Gang Wang and Xinyi Zhang and Shiliang Tang and
Christo Wilson and Haitao Zheng and Ben Y. Zhao",
title = "Clickstream User Behavior Models",
journal = j-TWEB,
volume = "11",
number = "4",
pages = "21:1--21:??",
month = sep,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3068332",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 15 08:22:45 MST 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The next generation of Internet services is driven by
users and user-generated content. The complex nature of
user behavior makes it highly challenging to manage and
secure online services. On one hand, service providers
cannot effectively prevent attackers from creating
large numbers of fake identities to disseminate
unwanted content (e.g., spam). On the other hand,
abusive behavior from real users also poses significant
threats (e.g., cyberbullying). In this article, we
propose clickstream models to characterize user
behavior in large online services. By analyzing
clickstream traces (i.e., sequences of click events
from users), we seek to achieve two goals: (1)
detection: to capture distinct user groups for the
detection of malicious accounts, and (2) understanding:
to extract semantic information from user groups to
understand the captured behavior. To achieve these
goals, we build two related systems. The first one is a
semisupervised system to detect malicious user accounts
(Sybils). The core idea is to build a clickstream
similarity graph where each node is a user and an edge
captures the similarity of two users' clickstreams.
Based on this graph, we propose a coloring scheme to
identify groups of malicious accounts without relying
on a large labeled dataset. We validate the system
using ground-truth clickstream traces of 16,000 real
and Sybil users from Renren, a large Chinese social
network. The second system is an unsupervised system
that aims to capture and understand the fine-grained
user behavior. Instead of binary classification
(malicious or benign), this model identifies the
natural groups of user behavior and automatically
extracts features to interpret their semantic meanings.
Applying this system to Renren and another online
social network, Whisper (100K users), we help service
providers identify unexpected user behaviors and even
predict users' future actions. Both systems received
positive feedback from our industrial collaborators
including Renren, LinkedIn, and Whisper after testing
on their internal clickstream data.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Hogan:2017:CFI,
author = "Aidan Hogan",
title = "Canonical Forms for Isomorphic and Equivalent {RDF}
Graphs: Algorithms for Leaning and Labelling Blank
Nodes",
journal = j-TWEB,
volume = "11",
number = "4",
pages = "22:1--22:??",
month = sep,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3068333",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 15 08:22:45 MST 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Existential blank nodes greatly complicate a number of
fundamental operations on Resource Description
Framework (RDF) graphs. In particular, the problems of
determining if two RDF graphs have the same structure
modulo blank node labels (i.e., if they are isomorphic
), or determining if two RDF graphs have the same
meaning under simple semantics (i.e., if they are
simple-equivalent ), have no known polynomial-time
algorithms. In this article, we propose methods that
can produce two canonical forms of an RDF graph. The
first canonical form preserves isomorphism such that
any two isomorphic RDF graphs will produce the same
canonical form; this iso-canonical form is produced by
modifying the well-known canonical labelling algorithm
N auty for application to RDF graphs. The second
canonical form additionally preserves
simple-equivalence such that any two simple-equivalent
RDF graphs will produce the same canonical form; this
equi-canonical form is produced by, in a preliminary
step, leaning the RDF graph, and then computing the
iso-canonical form. These algorithms have a number of
practical applications, such as for identifying
isomorphic or equivalent RDF graphs in a large
collection without requiring pairwise comparison, for
computing checksums or signing RDF graphs, for applying
consistent Skolemisation schemes where blank nodes are
mapped in a canonical manner to Internationalised
Resource Identifiers (IRIs), and so forth. Likewise a
variety of algorithms can be simplified by presupposing
RDF graphs in one of these canonical forms. Both
algorithms require exponential steps in the worst case;
in our evaluation we demonstrate that there indeed
exist difficult synthetic cases, but we also provide
results over 9.9 million RDF graphs that suggest such
cases occur infrequently in the real world, and that
both canonical forms can be efficiently computed in all
but a handful of such cases.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "22",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Koutrika:2017:SWP,
author = "Georgia Koutrika and Qian Lin",
title = "A Study of {Web} Print: What People Print in the
Digital Era",
journal = j-TWEB,
volume = "11",
number = "4",
pages = "23:1--23:??",
month = sep,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3068331",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 15 08:22:45 MST 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This article analyzes a proprietary log of printed web
pages and aims at answering questions regarding the
content people print (what), the reasons they print
(why), as well as attributes of their print profile
(who). We present a classification of pages printed
based on their print intent and we describe our
methodology for processing the print dataset used in
this study. In our analysis, we study the web sites,
topics, and print intent of the pages printed along the
following aspects: popularity, trends, activity, user
diversity, and consistency. We present several findings
that reveal interesting insights into printing. We
analyze our findings and discuss their impact and
directions for future work.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "23",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Bernaschi:2017:EAT,
author = "Massimo Bernaschi and Alessandro Celestini and Stefano
Guarino and Flavio Lombardi",
title = "Exploring and Analyzing the {Tor} Hidden Services
Graph",
journal = j-TWEB,
volume = "11",
number = "4",
pages = "24:1--24:??",
month = sep,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3008662",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 15 08:22:45 MST 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The exploration and analysis of Web graphs has
flourished in the recent past, producing a large number
of relevant and interesting research results. However,
the unique characteristics of the Tor network limit the
applicability of standard techniques and demand for
specific algorithms to explore and analyze it. The
attention of the research community has focused on
assessing the security of the Tor infrastructure (i.e.,
its ability to actually provide the intended level of
anonymity) and on discussing what Tor is currently
being used for. Since there are no foolproof techniques
for automatically discovering Tor hidden services,
little or no information is available about the
topology of the Tor Web graph. Even less is known on
the relationship between content similarity and
topological structure. The present article aims at
addressing such lack of information. Among its
contributions: a study on automatic Tor Web
exploration/data collection approaches; the adoption of
novel representative metrics for evaluating Tor data; a
novel in-depth analysis of the hidden services graph; a
rich correlation analysis of hidden services' semantics
and topology. Finally, a broad interesting set of novel
insights/considerations over the Tor Web organization
and content are provided.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "24",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Xu:2017:COF,
author = "Chang Xu and Jie Zhang",
title = "Collusive Opinion Fraud Detection in Online Reviews: a
Probabilistic Modeling Approach",
journal = j-TWEB,
volume = "11",
number = "4",
pages = "25:1--25:??",
month = sep,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3098859",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 15 08:22:45 MST 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We address the collusive opinion fraud problem in
online review portals, where groups of people work
together to deliver deceptive reviews for manipulating
the reputations of targeted items. Such collusive fraud
is considered much harder to defend against, since the
participants (or colluders) can evade detection by
shaping their behaviors collectively so as not to
appear suspicious. To alleviate this problem,
countermeasures have been proposed that leverage the
collective behaviors of colluders. The motivation stems
from the observation that colluders typically act in a
very synchronized way, as they are instructed by the
same campaigns with common items to target and
schedules to follow. However, the collective behaviors
examined in existing solutions focus mostly on the
external appearance of fraud campaigns, such as the
campaign size and the size of the targeted item set.
These signals may become ineffective once colluders
have changed their behaviors collectively. Moreover,
the detection algorithms used in existing approaches
are designed to only make collusion inference on the
input data; predictive models that can be deployed for
detecting emerging fraud cannot be learned from the
data. In this article, to complement existing studies
on collusive opinion fraud characterization and
detection, we explore more subtle behavioral trails in
collusive fraud practice. In particular, a suite of
homogeneity-based measures are proposed to capture the
interrelationships among colluders within campaigns.
Moreover, a novel statistical model is proposed to
further characterize, recognize, and predict collusive
fraud in online reviews. The proposed model is fully
unsupervised and highly flexible to incorporate
effective measures available for better modeling and
prediction. Through experiments on two real-world
datasets, we show that our method outperforms the state
of the art in both characterization and detection
abilities.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "25",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Chattopadhyay:2017:FSM,
author = "Soumi Chattopadhyay and Ansuman Banerjee and Nilanjan
Banerjee",
title = "A Fast and Scalable Mechanism for {Web} Service
Composition",
journal = j-TWEB,
volume = "11",
number = "4",
pages = "26:1--26:??",
month = sep,
year = "2017",
CODEN = "????",
DOI = "https://doi.org/10.1145/3098884",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Jan 15 08:22:45 MST 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In recent times, automated business processes and web
services have become ubiquitous in diverse application
spaces. Efficient composition of web services in real
time while providing necessary Quality of Service (QoS)
guarantees is a computationally complex problem and
several heuristic based approaches have been proposed
to compose the services optimally. In this article, we
present the design of a scalable QoS-aware service
composition mechanism that balances the computational
complexity of service composition with the QoS
guarantees of the composed service and achieves
scalability. Our design guarantees a single QoS
parameter using an intelligent search and pruning
mechanism in the composed service space. We also show
that our methodology yields near optimal solutions on
real benchmarks. We then enhance our proposed mechanism
to guarantee multiple QoS parameters using aggregation
techniques. Finally, we explore search time versus
solution quality tradeoff using parameterized search
algorithms that produce better-quality solutions at the
cost of delay. We present experimental results to show
the efficiency of our proposed mechanism.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "26",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{He:2018:EET,
author = "Ming He and Yong Ge and Enhong Chen and Qi Liu and
Xuesong Wang",
title = "Exploring the Emerging Type of Comment for Online
Videos: {DanMu}",
journal = j-TWEB,
volume = "12",
number = "1",
pages = "1:1--1:??",
month = feb,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3098885",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:00 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "DanMu, an emerging type of user-generated comment, has
become increasingly popular in recent years. Many
online video platforms such as Tudou.com have provided
the DanMu function. Unlike traditional online reviews
such as reviews at Youtube.com that are outside the
videos, DanMu is a scrolling marquee comment, which is
overlaid directly on top of the video and synchronized
to a specific playback time. Such comments are
displayed as streams of moving subtitles overlaid on
the video screen. Viewers could easily write DanMu s
while watching videos, and the written DanMu s will be
immediately overlaid onto the video and displayed to
writers themselves and other viewers as well. Such
DanMu systems have greatly enabled users to communicate
with each other in a much more direct way, creating a
real-time sharing experience. Although there are
several unique features of DanMu and has had a great
impact on online video systems, to the best of our
knowledge, there is no work that has provided a
comprehensive study on DanMu. In this article, as a
pilot study, we analyze the unique characteristics of
DanMu from various perspectives. Specifically, we first
illustrate some unique distributions of DanMu s by
comparing with traditional reviews (TReviews) that we
collected from a real DanMu -enabled online video
system. Second, we discover two interesting patterns in
DanMu data: a herding effect and multiple-burst
phenomena that are significantly different from those
in TRviews and reveal important insights about the
growth of DanMu s on a video. Towards exploring
antecedents of both th herding effect and
multiple-burst phenomena, we propose to further detect
leading DanMu s within bursts, because those leading
DanMu s make the most contribution to both patterns. A
framework is proposed to detect leading DanMu s that
effectively combines multiple factors contributing to
leading DanMu s. Based on the identified
characteristics of DanMu, finally we propose to predict
the distribution of future DanMu s (i.e., the growth of
DanMu s), which is important for many DanMu -enabled
online video systems, for example, the predicted DanMu
distribution could be an indicator of video popularity.
This prediction task includes two aspects: One is to
predict which videos future DanMu s will be posted for,
and the other one is to predict which segments of a
video future DanMu s will be posted on. We develop two
sophisticated models to solve both problems. Finally,
intensive experiments are conducted with a real-world
dataset to validate all methods developed in this
article.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Minervini:2018:AKP,
author = "Pasquale Minervini and Volker Tresp and Claudia
D'amato and Nicola Fanizzi",
title = "Adaptive Knowledge Propagation in {Web} Ontologies",
journal = j-TWEB,
volume = "12",
number = "1",
pages = "2:1--2:??",
month = feb,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3105961",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:00 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We focus on the problem of predicting missing
assertions in Web ontologies. We start from the
assumption that individual resources that are similar
in some aspects are more likely to be linked by
specific relations: this phenomenon is also referred to
as homophily and emerges in a variety of relational
domains. In this article, we propose a method for (1)
identifying which relations in the ontology are more
likely to link similar individuals and (2) efficiently
propagating knowledge across chains of similar
individuals. By enforcing sparsity in the model
parameters, the proposed method is able to select only
the most relevant relations for a given prediction
task. Our experimental evaluation demonstrates the
effectiveness of the proposed method in comparison to
state-of-the-art methods from the literature.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Liu:2018:RCW,
author = "Yining Liu and Yong Liu and Yanming Shen and Keqiu
Li",
title = "Recommendation in a Changing World: Exploiting
Temporal Dynamics in Ratings and Reviews",
journal = j-TWEB,
volume = "12",
number = "1",
pages = "3:1--3:??",
month = feb,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3108238",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:00 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Users' preferences, and consequently their ratings and
reviews to items, change over time. Likewise,
characteristics of items are also time-varying. By
dividing data into time periods, temporal Recommender
Systems (RSs) improve recommendation accuracy by
exploring the temporal dynamics in user rating data.
However, temporal RSs have to cope with rating sparsity
in each time period. Meanwhile, reviews generated by
users contain rich information about their preferences,
which can be exploited to address rating sparsity and
further improve the performance of temporal RSs. In
this article, we develop a temporal rating model with
topics that jointly mines the temporal dynamics of both
user-item ratings and reviews. Studying temporal drifts
in reviews helps us understand item rating evolutions
and user interest changes over time. Our model also
automatically splits the review text in each time
period into interim words and intrinsic words. By
linking interim words and intrinsic words to short-term
and long-term item features, respectively, we jointly
mine the temporal changes in user and item latent
features together with the associated review text in a
single learning stage. Through experiments on 28
real-world datasets collected from Amazon, we show that
the rating prediction accuracy of our model
significantly outperforms the existing state-of-art RS
models. And our model can automatically identify
representative interim words in each time period as
well as intrinsic words across all time periods. This
can be very useful in understanding the time evolution
of users' preferences and items' characteristics.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Tu:2018:ARP,
author = "Wenting Tu and David W. Cheung and Nikos Mamoulis and
Min Yang and Ziyu Lu",
title = "Activity Recommendation with Partners",
journal = j-TWEB,
volume = "12",
number = "1",
pages = "4:1--4:??",
month = feb,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3121407",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:00 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Recommending social activities, such as watching
movies or having dinner, is a common function found in
social networks or e-commerce sites. Besides certain
websites which manage activity-related locations (e.g.,
foursquare.com), many items on product sale platforms
(e.g., groupon.com) can naturally be mapped to social
activities. For example, movie tickets can be thought
of as activity items, which can be mapped as a social
activity of ``watch a movie.'' Traditional recommender
systems estimate the degree of interest for a target
user on candidate items (or activities), and
accordingly, recommend the top-$k$ activity items to
the user. However, these systems ignore an important
social characteristic of recommended activities: people
usually tend to participate in those activities with
friends. This article considers this fact for improving
the effectiveness of recommendation in two directions.
First, we study the problem of activity-partner
recommendation; i.e., for each recommended activity
item, find a suitable partner for the user. This (i)
saves the user's time for finding activity partners,
(ii) increases the likelihood that the activity item
will be selected by the user, and (iii) improves the
effectiveness of recommender systems to users overall
and enkindles their social enthusiasm. Our partner
recommender is built upon the users' historical
attendance preferences, their social context, and
geographic information. Moreover, we explore how to
leverage the partner recommendation to help improve the
effectiveness of recommending activities to users.
Assuming that users tend to select the activities for
which they can find suitable partners, we propose a
partner-aware activity recommendation model, which
integrates this hypothesis into conventional
recommendation approaches. Finally, the recommended
items not only match users' interests, but also have
high chances to be selected by the users, because the
users can find suitable partners to attend the
corresponding activities together. We conduct
experiments on real data to evaluate the effectiveness
of activity-partner recommendation and partner-aware
activity recommendation. The results verify that (i)
suggesting partners greatly improves the likelihood
that a recommended activity item is to be selected by
the target user and (ii) considering the existence of
suitable partners in the ranking of recommended items
improves the accuracy of recommendation
significantly.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Dutta:2018:CRM,
author = "Kaushik Dutta and Debra Vandermeer",
title = "Caching to Reduce Mobile App Energy Consumption",
journal = j-TWEB,
volume = "12",
number = "1",
pages = "5:1--5:??",
month = feb,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3125778",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:00 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Mobile applications consume device energy for their
operations, and the fast rate of battery depletion on
mobile devices poses a major usability hurdle. After
the display, data communication is the second-biggest
consumer of mobile device energy. At the same time,
software applications that run on mobile devices
represent a fast-growing product segment. Typically,
these applications serve as front-end display
mechanisms, which fetch data from remote servers and
display the information to the user in an appropriate
format-incurring significant data communication
overheads in the process. In this work, we propose
methods to reduce energy overheads in mobile devices
due to data communication by leveraging data caching
technology. A review of existing caching mechanisms
revealed that they are primarily designed for
optimizing response time performance and cannot be
easily ported to mobile devices for energy savings.
Further, architectural differences between traditional
client-server and mobile communications infrastructures
make the use of existing caching technologies
unsuitable in mobile devices. In this article, we
propose a set of two new caching approaches
specifically designed with the constraints of mobile
devices in mind: (a) a response caching approach and
(b) an object caching approach. Our experiments show
that, even for a small cache size of 250MB, object
caching can reduce energy consumption on average by
45\% compared to the no-cache case, and response
caching can reduce energy consumption by 20\% compared
to the no-cache case. The benefits increase with larger
cache sizes. These results demonstrate the efficacy of
our proposed method and raise the possibility of
significantly extending mobile device battery life.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Manta-Caro:2018:MSW,
author = "Cristyan Manta-Caro and Juan M. Fern{\'a}ndez-Luna",
title = "Modeling and Simulating the {Web of Things} from an
Information Retrieval Perspective",
journal = j-TWEB,
volume = "12",
number = "1",
pages = "6:1--6:??",
month = feb,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3132732",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:00 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Internet and Web technologies have changed our lives
in ways we are not yet fully aware of. In the near
future, Internet will interconnect more than 50 billion
things in the real world, nodes will sense billions of
features and properties of interest, and things will be
represented by web-based, bi-directional services with
highly dynamic content and real-time data. This is the
new era of the Internet and the Web of Things. Since
the emergence of such paradigms implies the evolution
and integration of the systems with which they
interact, it is essential to develop abstract models
for representing and simulating the Web of Things in
order to establish new approaches. This article
describes a Web of Things model based on a structured
XML representation. We also present a simulator whose
ultimate goal is to encapsulate the expected dynamics
of the Web of Things for the future development of
information retrieval (IR) systems. The simulator
generates a real-time collection of XML documents
containing spatio-temporal contexts and textual and
sensed information of highly dynamic dimensions. The
simulator is characterized by its flexibility and
versatility for representing real-world scenarios and
offers a unique perspective for information retrieval.
In this article, we evaluate and test the simulator in
terms of its performance variables for computing
resource consumption and present our experimentation
with the simulator on three real scenarios by
considering the generation variables for the IR
document collection.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Davison:2018:LTR,
author = "Brian D. Davison",
title = "List of 2016 {TWEB} Reviewers",
journal = j-TWEB,
volume = "12",
number = "1",
pages = "7:1--7:??",
month = feb,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3180440",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:00 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Davison:2018:E,
author = "Brian D. Davison",
title = "Editorial",
journal = j-TWEB,
volume = "12",
number = "2",
pages = "8:1--8:??",
month = jun,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3232925",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:01 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8e",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Jia:2018:KGE,
author = "Yantao Jia and Yuanzhuo Wang and Xiaolong Jin and
Hailun Lin and Xueqi Cheng",
title = "Knowledge Graph Embedding: a Locally and Temporally
Adaptive Translation-Based Approach",
journal = j-TWEB,
volume = "12",
number = "2",
pages = "8:1--8:??",
month = jun,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3132733",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:01 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "A knowledge graph is a graph with entities of
different types as nodes and various relations among
them as edges. The construction of knowledge graphs in
the past decades facilitates many applications, such as
link prediction, web search analysis, question
answering, and so on. Knowledge graph embedding aims to
represent entities and relations in a large-scale
knowledge graph as elements in a continuous vector
space. Existing methods, for example, TransE, TransH,
and TransR, learn the embedding representation by
defining a global margin-based loss function over the
data. However, the loss function is determined during
experiments whose parameters are examined among a
closed set of candidates. Moreover, embeddings over two
knowledge graphs with different entities and relations
share the same set of candidates, ignoring the locality
of both graphs. This leads to the limited performance
of embedding related applications. In this article, a
locally adaptive translation method for knowledge graph
embedding, called TransA, is proposed to find the loss
function by adaptively determining its margin over
different knowledge graphs. Then the convergence of
TransA is verified from the aspect of its uniform
stability. To make the embedding methods up-to-date
when new vertices and edges are added into the
knowledge graph, the incremental algorithm for TransA,
called iTransA, is proposed by adaptively adjusting the
optimal margin over time. Experiments on four benchmark
data sets demonstrate the superiority of the proposed
method, as compared to the state-of-the-art ones.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Park:2018:WSD,
author = "Souneil Park and Aleksandar Matic and Kamini Garg and
Nuria Oliver",
title = "When Simpler Data Does Not Imply Less Information: a
Study of User Profiling Scenarios With Constrained View
of Mobile {HTTP(S)} Traffic",
journal = j-TWEB,
volume = "12",
number = "2",
pages = "9:1--9:??",
month = jun,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3143402",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:01 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The exponential growth in smartphone adoption is
contributing to the availability of vast amounts of
human behavioral data. This data enables the
development of increasingly accurate data-driven user
models that facilitate the delivery of personalized
services that are often free in exchange for the use of
its customers' data. Although such usage conventions
have raised many privacy concerns, the increasing value
of personal data is motivating diverse entities to
aggressively collect and exploit the data. In this
article, we unfold profiling scenarios around mobile
HTTP(S) traffic, focusing on those that have limited
but meaningful segments of the data. The capability of
the scenarios to profile personal information is
examined with real user data, collected in the wild
from 61 mobile phone users for a minimum of 30 days.
Our study attempts to model heterogeneous user traits
and interests, including personality, boredom
proneness, demographics, and shopping interests. Based
on our modeling results, we discuss various
implications to personalization, privacy, and personal
data rights.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Calzavara:2018:SBA,
author = "Stefano Calzavara and Alvise Rabitti and Michele
Bugliesi",
title = "Semantics-Based Analysis of Content Security Policy
Deployment",
journal = j-TWEB,
volume = "12",
number = "2",
pages = "10:1--10:??",
month = jun,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3149408",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:01 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Content Security Policy (CSP) is a recent W3C standard
introduced to prevent and mitigate the impact of
content injection vulnerabilities on websites. In this
article, we introduce a formal semantics for the latest
stable version of the standard, CSP Level 2. We then
perform a systematic, large-scale analysis of the
effectiveness of the current CSP deployment, using the
formal semantics to substantiate our methodology and to
assess the impact of the detected issues. We focus on
four key aspects that affect the effectiveness of CSP:
browser support, website adoption, correct
configuration, and constant maintenance. Our analysis
shows that browser support for CSP is largely
satisfactory, with the exception of a few notable
issues. However, there are several shortcomings
relative to the other three aspects. CSP appears to
have a rather limited deployment as yet and, more
crucially, existing policies exhibit a number of
weaknesses and misconfiguration errors. Moreover,
content security policies are not regularly updated to
ban insecure practices and remove unintended security
violations. We argue that many of these problems can be
fixed by better exploiting the monitoring facilities of
CSP, while other issues deserve additional research,
being more rooted into the CSP design.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cacheda:2018:CPU,
author = "Fidel Cacheda and Roi Blanco and Nicola Barbieri",
title = "Characterizing and Predicting Users' Behavior on Local
Search Queries",
journal = j-TWEB,
volume = "12",
number = "2",
pages = "11:1--11:??",
month = jun,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3157059",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:01 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The use of queries to find products and services that
are located nearby is increasing rapidly due mainly to
the ubiquity of internet access and location services
provided by smartphone devices. Local search engines
help users by matching queries with a predefined
geographical connotation (``local queries'') against a
database of local business listings. Local search
differs from traditional Web search because, to
correctly capture users' click behavior, the estimation
of relevance between query and candidate results must
be integrated with geographical signals, such as
distance. The intuition is that users prefer businesses
that are physically closer to them or in a convenient
area (e.g., close to their home). However, this notion
of closeness depends upon other factors, like the
business category, the quality of the service provided,
the density of businesses in the area of interest, the
hour of the day, or even the day of the week. In this
work, we perform an extensive analysis of online users'
interactions with a local search engine, investigating
their intent, temporal patterns, and highlighting
relationships between distance-to-business and other
factors, such as business reputation, Furthermore, we
investigate the problem of estimating the click-through
rate on local search ( LCTR ) by exploiting the
combination of standard retrieval methods with a rich
collection of geo-, user-, and business-dependent
features. We validate our approach on a large log
collected from a real-world local search service. Our
evaluation shows that the non-linear combination of
business and user information, geo-local and textual
relevance features leads to a significant improvements
over existing alternative approaches based on a
combination of relevance, distance, and business
reputation [1].",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Boldi:2018:BMC,
author = "Paolo Boldi and Andrea Marino and Massimo Santini and
Sebastiano Vigna",
title = "{BUbiNG}: Massive Crawling for the Masses",
journal = j-TWEB,
volume = "12",
number = "2",
pages = "12:1--12:26",
month = jun,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3160017",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:01 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/java2010.bib;
http://www.math.utah.edu/pub/tex/bib/pagerank.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/citation.cfm?doid=3176641.3160017",
abstract = "Although web crawlers have been around for twenty
years by now, there is virtually no freely available,
open-source crawling software that guarantees high
throughput, overcomes the limits of single-machine
systems, and, at the same time, scales linearly with
the amount of resources available. This article aims at
filling this gap, through the description of BUbiNG,
our next-generation web crawler built upon the authors'
experience with UbiCrawler [9] and on the last ten
years of research on the topic. BUbiNG is an
open-source Java fully distributed crawler; a single
BUbiNG agent, using sizeable hardware, can crawl
several thousand pages per second respecting strict
politeness constraints, both host- and IP-based. Unlike
existing open-source distributed crawlers that rely on
batch techniques (like MapReduce), BUbiNG job
distribution is based on modern high-speed protocols to
achieve very high throughput.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
keywords = "BUbiNG; centrality measures; distributed systems;
Java; PageRank; UbiCrawler; Web crawling",
}
@Article{Gaeta:2018:MID,
author = "Rossano Gaeta",
title = "A Model of Information Diffusion in Interconnected
Online Social Networks",
journal = j-TWEB,
volume = "12",
number = "2",
pages = "13:1--13:??",
month = jun,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3160000",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:01 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Online social networks (OSN) have today reached a
remarkable capillary diffusion. There are numerous
examples of very large platforms people use to
communicate and maintain relationships. People also
subscribe to several OSNs, e.g., people create accounts
on Facebook, Twitter, and so on. This phenomenon leads
to online social internetworking (OSI) scenarios where
users who subscribe to multiple OSNs are termed as
bridges. Unfortunately, several important features make
the study of information propagation in an OSI scenario
a difficult task, e.g., correlations in both the
structural characteristics of OSNs and the bridge
interconnections among them, heterogeneity and size of
OSNs, activity factors, cross-posting propensity, and
so on. In this article, we propose a directed random
graph-based model that is amenable to efficient
numerical solution to analyze the phenomenon of
information propagation in an OSI scenario; in the
model development, we take into account heterogeneity
and correlations introduced by both topological
(correlations among nodes degrees and among bridge
distributions) and user-related factors (activity
index, cross-posting propensity). We first validate the
model predictions against simulations on snapshots of
interconnected OSNs in a reference scenario.
Subsequently, we exploit the model to show the impact
on the information propagation of several
characteristics of the reference scenario, i.e., size
and complexity of the OSI scenario, degree distribution
and overall number of bridges, growth and decline of
OSNs in time, and time-varying cross-posting users
propensity.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Davison:2018:TR,
author = "Brian D. Davison",
title = "2017 {TWEB} Reviewers",
journal = j-TWEB,
volume = "12",
number = "2",
pages = "14:1--14:??",
month = jun,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3209033",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jun 28 14:10:01 MDT 2018",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Fogli:2018:EQU,
author = "Daniela Fogli and Giovanni Guida",
title = "Evaluating Quality in Use of Corporate {Web} Sites: an
Empirical Investigation",
journal = j-TWEB,
volume = "12",
number = "3",
pages = "15:1--15:??",
month = jul,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3184646",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In our prior work, we presented a novel approach to
the evaluation of quality in use of corporate web sites
based on an original quality model (QM-U) and a related
methodology (EQ-EVAL). This article focuses on two
research questions. The first one aims at investigating
whether expected quality obtained through the
application of EQ-EVAL methodology by employing a small
panel of evaluators is a good approximation of actual
quality obtained through experimentation with real
users. To answer this research question, a comparative
study has been carried out involving 5 evaluators and
50 real users. The second research question aims at
demonstrating that the adoption of the EQ-EVAL
methodology can provide useful information for web site
improvement. Three original indicators, namely
coherence, coverage and ranking have been defined to
answer this question, and an additional study comparing
the assessments of two panels of 5 and 10 evaluators,
respectively, has been carried out. The results
obtained in both studies are largely positive and
provide a rational support for the adoption of the
EQ-EVAL methodology.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Park:2018:LLB,
author = "Sangkeun Park and Mark S. Ackerman and Uichin Lee",
title = "Localness of Location-based Knowledge Sharing: a Study
of {Naver KiN} {``Here''}",
journal = j-TWEB,
volume = "12",
number = "3",
pages = "16:1--16:??",
month = jul,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/2983645",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "In location-based social Q8A services, people ask a
question with a high expectation that local residents
who have local knowledge will answer the question.
However, little is known about the locality of user
activities in location-based social Q8A services. This
study aims to deepen our understanding of
location-based knowledge sharing by investigating the
following: general behavioral characteristics of users,
the topical and typological patterns related to
geographic characteristics, geographic locality of user
activities, and motivations of local knowledge sharing.
To this end, we analyzed a 12-month period Q8A dataset
from Naver KiN ``Here,'' a location-based social Q8A
mobile app, in addition to a supplementary survey
dataset obtained from 285 mobile users. Our results
reveal several unique characteristics of location-based
social Q8A. When compared with conventional social Q8A
sites, users ask and answer different
topical/typological questions. In addition, those who
answer have a strong spatial locality wherein they
primarily have local knowledge in a few regions, in
areas such as their home and work. We also find unique
motivators such as ownership of local knowledge and a
sense of local community. The findings reported in the
article have significant implications for the design of
Q8A systems, especially location-based social Q8A
systems.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Rudra:2018:ESS,
author = "Koustav Rudra and Niloy Ganguly and Pawan Goyal and
Saptarshi Ghosh",
title = "Extracting and Summarizing Situational Information
from the {Twitter} Social Media during Disasters",
journal = j-TWEB,
volume = "12",
number = "3",
pages = "17:1--17:??",
month = jul,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3178541",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Microblogging sites like Twitter have become important
sources of real-time information during disaster
events. A large amount of valuable situational
information is posted in these sites during disasters;
however, the information is dispersed among hundreds of
thousands of tweets containing sentiments and opinions
of the masses. To effectively utilize microblogging
sites during disaster events, it is necessary to not
only extract the situational information from the large
amounts of sentiments and opinions, but also to
summarize the large amounts of situational information
posted in real-time. During disasters in countries like
India, a sizable number of tweets are posted in local
resource-poor languages besides the normal
English-language tweets. For instance, in the Indian
subcontinent, a large number of tweets are posted in
Hindi/Devanagari (the national language of India), and
some of the information contained in such non-English
tweets is not available (or available at a later point
of time) through English tweets. In this work, we
develop a novel classification-summarization framework
which handles tweets in both English and Hindi-we first
extract tweets containing situational information, and
then summarize this information. Our proposed
methodology is developed based on the understanding of
how several concepts evolve in Twitter during disaster.
This understanding helps us achieve superior
performance compared to the state-of-the-art tweet
classifiers and summarization approaches on English
tweets. Additionally, to our knowledge, this is the
first attempt to extract situational information from
non-English tweets.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Darari:2018:CMR,
author = "Fariz Darari and Werner Nutt and Giuseppe Pirr{\`o}
and Simon Razniewski",
title = "Completeness Management for {RDF} Data Sources",
journal = j-TWEB,
volume = "12",
number = "3",
pages = "18:1--18:??",
month = jul,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3196248",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The Semantic Web is commonly interpreted under the
open-world assumption, meaning that information
available (e.g., in a data source) captures only a
subset of the reality. Therefore, there is no certainty
about whether the available information provides a
complete representation of the reality. The broad aim
of this article is to contribute a formal study of how
to describe the completeness of parts of the Semantic
Web stored in RDF data sources. We introduce a
theoretical framework allowing augmentation of RDF data
sources with statements, also expressed in RDF, about
their completeness. One immediate benefit of this
framework is that now query answers can be complemented
with information about their completeness. We study the
impact of completeness statements on the complexity of
query answering by considering different fragments of
the SPARQL language, including the RDFS entailment
regime, and the federated scenario. We implement an
efficient method for reasoning about query completeness
and provide an experimental evaluation in the presence
of large sets of completeness statements.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wang:2018:OWP,
author = "Yue Wang and Dawei Yin and Luo Jie and Pengyuan Wang
and Makoto Yamada and Yi Chang and Qiaozhu Mei",
title = "Optimizing Whole-Page Presentation for {Web} Search",
journal = j-TWEB,
volume = "12",
number = "3",
pages = "19:1--19:??",
month = jul,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3204461",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Modern search engines aggregate results from different
verticals: webpages, news, images, video, shopping,
knowledge cards, local maps, and so on. Unlike ``ten
blue links,'' these search results are heterogeneous in
nature and not even arranged in a list on the page.
This revolution directly challenges the conventional
``ranked list'' formulation in ad hoc search.
Therefore, finding proper presentation for a gallery of
heterogeneous results is critical for modern search
engines. We propose a novel framework that learns the
optimal page presentation to render heterogeneous
results onto search result page (SERP). Page
presentation is broadly defined as the strategy to
present a set of items on SERP, much more expressive
than a ranked list. It can specify item positions,
image sizes, text fonts, and any other styles as long
as variations are within business and design
constraints. The learned presentation is content aware,
i.e., tailored to specific queries and returned
results. Simulation experiments show that the framework
automatically learns eye-catchy presentations for
relevant results. Experiments on real data show that
simple instantiations of the framework already
outperform leading algorithm in federated search result
presentation. It means the framework can learn its own
result presentation strategy purely from data, without
even knowing the ``probability ranking principle.''",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Mula:2018:FBE,
author = "Wojciech Mu{\l}a and Daniel Lemire",
title = "Faster {Base64} Encoding and Decoding Using {AVX2}
Instructions",
journal = j-TWEB,
volume = "12",
number = "3",
pages = "20:1--20:??",
month = jul,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3132709",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/java2010.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Web developers use base64 formats to include images,
fonts, sounds, and other resources directly inside
HTML, JavaScript, JSON, and XML files. We estimate that
billions of base64 messages are decoded every day. We
are motivated to improve the efficiency of base64
encoding and decoding. Compared to state-of-the-art
implementations, we multiply the speeds of both the
encoding ( \approx 10 $ \times $0) and the decoding (
\approx 7 $ \times $). We achieve these good results by
using the single-instruction-multiple-data instructions
available on recent Intel processors (AVX2). Our
accelerated software abides by the specification and
reports errors when encountering characters outside of
the base64 set. It is available online as free software
under a liberal license.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Parisi:2018:TUD,
author = "Francesco Parisi and Noseong Park and Andrea Pugliese
and V. S. Subrahmanian",
title = "Top-$k$ User-Defined Vertex Scoring Queries in
Edge-Labeled Graph Databases",
journal = j-TWEB,
volume = "12",
number = "4",
pages = "21:1--21:??",
month = nov,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3213891",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We consider identifying highly ranked vertices in
large graph databases such as social networks or the
Semantic Web where there are edge labels. There are
many applications where users express scoring queries
against such databases that involve two elements: (i) a
set of patterns describing relationships that a vertex
of interest to the user must satisfy and (ii) a scoring
mechanism in which the user may use properties of the
vertex to assign a score to that vertex. We define the
concept of a partial pattern map query (partial
PM-query), which intuitively allows us to prune partial
matchings, and show that finding an optimal partial
PM-query is NP-hard. We then propose two algorithms,
PScore\_LP and PScore\_NWST, to find the answer to a
scoring (top- k ) query. In PScore\_LP, the optimal
partial PM-query is found using a list-oriented pruning
method. PScore\_NWST leverages node-weighted Steiner
trees to quickly compute slightly sub-optimal
solutions. We conduct detailed experiments comparing
our algorithms with (i) an algorithm (PScore\_Base)
that computes all answers to the query, evaluates them
according to the scoring method, and chooses the top-
k, and (ii) two Semantic Web query processing systems
(Jena and GraphDB). Our algorithms show better
performance than PScore\_Base and the Semantic Web
query processing systems-moreover, PScore\_NWST
outperforms PScore\_LP on large queries and on queries
with a tree structure.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Fanou:2018:EAA,
author = "Rod{\'e}rick Fanou and Gareth Tyson and Eder Leao
Fernandes and Pierre Francois and Francisco Valera and
Arjuna Sathiaseelan",
title = "Exploring and Analysing the {African} {Web}
Ecosystem",
journal = j-TWEB,
volume = "12",
number = "4",
pages = "22:1--22:??",
month = nov,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3213897",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "It is well known that internet infrastructure
deployment is progressing at a rapid pace in the
African continent. A flurry of recent research has
quantified this, highlighting the expansion of its
underlying connectivity network. However, improving the
infrastructure is not useful without appropriately
provisioned services to exploit it. This article
measures the availability and utilisation of web
infrastructure in Africa. Whereas others have explored
web infrastructure in developed regions, we shed light
on practices in developing regions. To achieve this, we
apply a comprehensive measurement methodology to
collect data from a variety of sources. We first focus
on Google to reveal that its content infrastructure in
Africa is, indeed, expanding. That said, we find that
much of its web content is still served from the US and
Europe, despite being the most popular website in many
African countries. We repeat the same analysis across a
number of other regionally popular websites to find
that even top African websites prefer to host their
content abroad. To explore the reasons for this, we
evaluate some of the major bottlenecks facing content
delivery networks (CDNs) in Africa. Amongst other
factors, we find a lack of peering between the networks
hosting our probes, preventing the sharing of CDN
servers, as well as poorly configured DNS resolvers.
Finally, our mapping of middleboxes in the region
reveals that there is a greater presence of transparent
proxies in Africa than in Europe or the US. We conclude
the work with a number of suggestions for alleviating
the issues observed.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "22",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Torre-Bastida:2018:RBT,
author = "Ana I. Torre-Bastida and Jes{\'u}s Berm{\'u}dez and
Arantza Illarramendi",
title = "A Rule-Based Transducer for Querying Incompletely
Aligned Datasets",
journal = j-TWEB,
volume = "12",
number = "4",
pages = "23:1--23:??",
month = nov,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3228328",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "A growing number of Linked Open Data sources (from
diverse provenances and about different domains) that
can be freely browsed and searched to find and extract
useful information have been made available. However,
access to them is difficult for different reasons. This
study addresses access issues concerning heterogeneity.
It is common for datasets to describe the same or
overlapping domains while using different vocabularies.
Our study presents a transducer that transforms a
SPARQL query suitably expressed in terms of the
vocabularies used in a source dataset into another
SPARQL query suitably expressed for a target dataset
involving different vocabularies. The transformation is
based on existing alignments between terms in different
datasets. Whenever the transducer is unable to produce
a semantically equivalent query because of the scarcity
of term alignments, the transducer produces a semantic
approximation of the query to avoid returning the empty
answer to the user. Transformation across datasets is
achieved through the management of a wide range of
transformation rules. The feasibility of our proposal
has been validated with a prototype implementation that
processes queries that appear in well-known benchmarks
and SPARQL endpoint logs. Results of the experiments
show that the system is quite effective in achieving
adequate transformations.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "23",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Vassio:2018:YWY,
author = "Luca Vassio and Idilio Drago and Marco Mellia and Zied
{Ben Houidi} and Mohamed Lamine Lamali",
title = "You, the {Web}, and Your Device: Longitudinal
Characterization of Browsing Habits",
journal = j-TWEB,
volume = "12",
number = "4",
pages = "24:1--24:??",
month = nov,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3231466",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Understanding how people interact with the web is key
for a variety of applications, e.g., from the design of
effective web pages to the definition of successful
online marketing campaigns. Browsing behavior has been
traditionally represented and studied by means of
clickstreams, i.e., graphs whose vertices are web
pages, and edges are the paths followed by users.
Obtaining large and representative data to extract
clickstreams is, however, challenging. The evolution of
the web questions whether browsing behavior is changing
and, by consequence, whether properties of clickstreams
are changing. This article presents a longitudinal
study of clickstreams from 2013 to 2016. We evaluate an
anonymized dataset of HTTP traces captured in a large
ISP, where thousands of households are connected. We
first propose a methodology to identify actual URLs
requested by users from the massive set of requests
automatically fired by browsers when rendering web
pages. Then, we characterize web usage patterns and
clickstreams, taking into account both the temporal
evolution and the impact of the device used to explore
the web. Our analyses precisely quantify various
aspects of clickstreams and uncover interesting
patterns, such as the typical short paths followed by
people while navigating the web, the fast increasing
trend in browsing from mobile devices, and the
different roles of search engines and social networks
in promoting content. Finally, we contribute a dataset
of anonymized clickstreams to the community to foster
new studies.\<sup;\>1\</sup;\>",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "24",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Gong:2018:UCS,
author = "Qingyuan Gong and Yang Chen and Jiyao Hu and Qiang Cao
and Pan Hui and Xin Wang",
title = "Understanding Cross-Site Linking in Online Social
Networks",
journal = j-TWEB,
volume = "12",
number = "4",
pages = "25:1--25:??",
month = nov,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3213898",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "As a result of the blooming of online social networks
(OSNs), a user often holds accounts on multiple sites.
In this article, we study the emerging ``cross-site
linking'' function available on mainstream OSN services
including Foursquare, Quora, and Pinterest. We first
conduct a data-driven analysis on crawled profiles and
social connections of all 61.39 million Foursquare
users to obtain a thorough understanding of this
function. Our analysis has shown that the cross-site
linking function is adopted by 57.10\% of all
Foursquare users, and the users who have enabled this
function are more active than others. We also find that
the enablement of cross-site linking might lead to
privacy risks. Based on cross-site links between
Foursquare and external OSN sites, we formulate
cross-site information aggregation as a problem that
uses cross-site links to stitch together site-local
information fields for OSN users. Using large datasets
collected from Foursquare, Facebook, and Twitter, we
demonstrate the usefulness and the challenges of
cross-site information aggregation. In addition to the
measurements, we carry out a survey collecting detailed
user feedback on cross-site linking. This survey
studies why people choose to or not to enable
cross-site linking, as well as the motivation and
concerns of enabling this function.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "25",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cui:2018:UDR,
author = "Yi Cui and Clint Sparkman and Hsin-Tsang Lee and
Dmitri Loguinov",
title = "Unsupervised Domain Ranking in Large-Scale {Web}
Crawls",
journal = j-TWEB,
volume = "12",
number = "4",
pages = "26:1--26:??",
month = nov,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3182180",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/pagerank.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "With the proliferation of web spam and infinite
autogenerated web content, large-scale web crawlers
require low-complexity ranking methods to effectively
budget their limited resources and allocate bandwidth
to reputable sites. In this work, we assume crawls that
produce frontiers orders of magnitude larger than RAM,
where sorting of pending URLs is infeasible in real
time. Under these constraints, the main objective is to
quickly compute domain budgets and decide which of them
can be massively crawled. Those ranked at the top of
the list receive aggressive crawling allowances, while
all other domains are visited at some small default
rate. To shed light on Internet-wide spam avoidance, we
study topology-based ranking algorithms on domain-level
graphs from the two largest academic crawls: a
6.3B-page IRLbot dataset and a 1B-page ClueWeb09
exploration. We first propose a new methodology for
comparing the various rankings and then show that
in-degree BFS-based techniques decisively outperform
classic PageRank-style methods, including TrustRank.
However, since BFS requires several orders of magnitude
higher overhead and is generally infeasible for
real-time use, we propose a fast, accurate, and
scalable estimation method called TSE that can achieve
much better crawl prioritization in practice. It is
especially beneficial in applications with limited
hardware resources.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "26",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{An:2018:IPR,
author = "J. An and H. Kwak and S. Jung and J. Salminen and M.
Admad and B. Jansen",
title = "Imaginary People Representing Real Numbers: Generating
Personas from Online Social Media Data",
journal = j-TWEB,
volume = "12",
number = "4",
pages = "27:1--27:??",
month = nov,
year = "2018",
CODEN = "????",
DOI = "https://doi.org/10.1145/3265986",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "We develop a methodology to automate creating
imaginary people, referred to as personas, by
processing complex behavioral and demographic data of
social media audiences. From a popular social media
account containing more than 30 million interactions by
viewers from 198 countries engaging with more than
4,200 online videos produced by a global media
corporation, we demonstrate that our methodology has
several novel accomplishments, including: (a)
identifying distinct user behavioral segments based on
the user content consumption patterns; (b) identifying
impactful demographics groupings; and (c) creating rich
persona descriptions by automatically adding pertinent
attributes, such as names, photos, and personal
characteristics. We validate our approach by
implementing the methodology into an actual working
system; we then evaluate it via quantitative methods by
examining the accuracy of predicting content preference
of personas, the stability of the personas over time,
and the generalizability of the method via applying to
two other datasets. Research findings show the approach
can develop rich personas representing the behavior and
demographics of real audiences using privacy-preserving
aggregated online social media data from major online
platforms. Results have implications for media
companies and other organizations distributing content
via online platforms.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "27",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Wilson:2019:APP,
author = "Shomir Wilson and Florian Schaub and Frederick Liu and
Kanthashree Mysore Sathyendra and Daniel Smullen and
Sebastian Zimmeck and Rohan Ramanath and Peter Story
and Fei Liu and Norman Sadeh and Noah A. Smith",
title = "Analyzing Privacy Policies at Scale: From
Crowdsourcing to Automated Annotations",
journal = j-TWEB,
volume = "13",
number = "1",
pages = "1:1--1:??",
month = feb,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3230665",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Website privacy policies are often long and difficult
to understand. While research shows that Internet users
care about their privacy, they do not have the time to
understand the policies of every website they visit,
and most users hardly ever read privacy policies. Some
recent efforts have aimed to use a combination of
crowdsourcing, machine learning, and natural language
processing to interpret privacy policies at scale, thus
producing annotations for use in interfaces that inform
Internet users of salient policy details. However,
little attention has been devoted to studying the
accuracy of crowdsourced privacy policy annotations,
how crowdworker productivity can be enhanced for such a
task, and the levels of granularity that are feasible
for automatic analysis of privacy policies. In this
article, we present a trajectory of work addressing
each of these topics. We include analyses of
crowdworker performance, evaluation of a method to make
a privacy-policy oriented task easier for crowdworkers,
a coarse-grained approach to labeling segments of
policy text with descriptive themes, and a fine-grained
approach to identifying user choices described in
policy text. Together, the results from these efforts
show the effectiveness of using automated and
semi-automated methods for extracting from privacy
policies the data practice details that are salient to
Internet users' interests.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Athanasopoulos:2019:MAX,
author = "Dionysis Athanasopoulos and Apostolos Zarras",
title = "Mining Abstract {XML} Data-Types",
journal = j-TWEB,
volume = "13",
number = "1",
pages = "2:1--2:??",
month = feb,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3267467",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Schema integration has been a long-standing challenge
for the data-engineering community that has received
steady attention over the past three decades.
General-purpose integration approaches construct
unified schemas that encompass all schema elements.
Schema integration has been revisited in the past
decade in service-oriented computing since the
input/output data-types of service interfaces are
heterogeneous XML schemas. However, service integration
differs from the traditional integration problem, since
it should generalize schemas (mining abstract
data-types) instead of unifying all schema elements. To
mine well-formed abstract data-types, the fundamental
Liskov Substitution Principle (LSP), which generally
holds between abstract data-types and their subtypes,
should be followed. However, due to the heterogeneity
of service data-types, the strict employment of LSP is
not usually feasible. On top of that, XML offers a rich
type system, based on which data-types are defined via
combining type patterns (e.g., composition,
aggregation). The existing integration approaches have
not dealt with the challenges of a defining subtyping
relation between XML type patterns. To address these
challenges, we propose a relaxed version of LSP between
XML type patterns and an automated generalization
process for mining abstract XML data-types. We evaluate
the effectiveness and the efficiency of the process on
the schemas of two datasets against two representative
state-of-the-art approaches.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Anisetti:2019:TBS,
author = "Marco Anisetti and Claudio Ardagna and Ernesto Damiani
and Gianluca Polegri",
title = "Test-Based Security Certification of Composite
Services",
journal = j-TWEB,
volume = "13",
number = "1",
pages = "3:1--3:??",
month = feb,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3267468",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "The diffusion of service-based and cloud-based systems
has created a scenario where software is often made
available as services, offered as commodities over
corporate networks or the global net. This scenario
supports the definition of business processes as
composite services, which are implemented via either
static or runtime composition of offerings provided by
different suppliers. Fast and accurate evaluation of
services' security properties becomes then a
fundamental requirement and is nowadays part of the
software development process. In this article, we show
how the verification of security properties of
composite services can be handled by test-based
security certification and built to be effective and
efficient in dynamic composition scenarios. Our
approach builds on existing security certification
schemes for monolithic services and extends them
towards service compositions. It virtually certifies
composite services, starting from certificates awarded
to the component services. We describe three heuristic
algorithms for generating runtime test-based evidence
of the composite service holding the properties. These
algorithms are compared with the corresponding
exhaustive algorithm to evaluate their quality and
performance. We also evaluate the proposed approach in
a real-world industrial scenario, which considers
ENGpay online payment system of Engineering Ingegneria
Informatica S.p.A. The proposed industrial evaluation
presents the utility and generality of the proposed
approach by showing how certification results can be
used as a basis to establish compliance to Payment Card
Industry Data Security Standard.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Redmiles:2019:NPW,
author = "Elissa M. Redmiles and Eszter Hargittai",
title = "New Phone, Who Dis? {Modeling} Millennials' Backup
Behavior",
journal = j-TWEB,
volume = "13",
number = "1",
pages = "4:1--4:??",
month = feb,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3208105",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Given the ever-rising frequency of malware attacks and
other problems leading people to lose their files,
backups are an important proactive protective behavior
in which users can engage. Backing up files can prevent
emotional and financial losses and improve overall user
experience. Yet, we find that less than half of young
adults perform mobile or computer backups regularly. To
understand why, we model the factors that drive mobile
and computer backup behavior, and changes in that
behavior over time, using data from a panel survey of
384 diverse young adults. We develop a set of models
that explain 37\% and 38\% of the variance in reported
mobile and computer backup behaviors, respectively.
These models show consistent relationships between
Internet skills and backup frequency on both mobile and
computer devices. We find that this relationship holds
longitudinally: increases in Internet skills lead to
increased frequency of computer backups. This article
provides a foundation for understanding what drives
young adults' backup behavior. It concludes with
recommendations for motivating people to back up, and
for future work, modeling similar user behaviors.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Calegari:2019:WPH,
author = "Patrice Calegari and Marc Levrier and Pawe{\l}
Balczy{\'n}ski",
title = "{Web} Portals for High-performance Computing: a
Survey",
journal = j-TWEB,
volume = "13",
number = "1",
pages = "5:1--5:??",
month = feb,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3197385",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/java2010.bib;
http://www.math.utah.edu/pub/tex/bib/super.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "This article addresses web interfaces for
High-performance Computing (HPC) simulation software.
First, it presents a brief history, starting in the
1990s with Java applets, of web interfaces used for
accessing and making best possible use of remote HPC
resources. It introduces HPC web-based portal use
cases. Then it identifies and discusses the key
features, among functional and non-functional
requirements, that characterize such portals. A brief
state of the art is then presented. The design and
development of Bull extreme factory Computing Studio v3
(XCS3) is chosen as a common thread for showing how the
identified key features can all be implemented in one
software: multi-tenancy, multi-scheduler compatibility,
complete control through an HTTP RESTful API,
customizable user interface with Responsive Web Design,
HPC application template framework, remote
visualization, and access through the Authentication,
Authorization, and Accounting security framework with
the Role-Based Access Control permission model.
Non-functional requirements (security, usability,
performance, reliability) are discussed, and the
article concludes by giving perspective for future
work.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Romero:2019:SNU,
author = "Daniel M. Romero and Brian Uzzi and Jon Kleinberg",
title = "Social Networks under Stress: Specialized Team Roles
and Their Communication Structure",
journal = j-TWEB,
volume = "13",
number = "1",
pages = "6:1--6:??",
month = feb,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3295460",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Social network research has begun to take advantage of
fine-grained communications regarding coordination,
decision-making, and knowledge sharing. These studies,
however, have not generally analyzed how external
events are associated with a social network's structure
and communicative properties. Here, we study how
external events are associated with a network's change
in structure and communications. Analyzing a complete
dataset of millions of instant messages among the
decision-makers with different roles in a large hedge
fund and their network of outside contacts, we
investigate the link between price shocks, network
structure, and change in the affect and cognition of
decision-makers embedded in the network. We also
analyze the communication dynamics among specialized
teams in the organization. When price shocks occur the
communication network tends not to display structural
changes associated with adaptiveness such as the
activation of weak ties to obtain novel information.
Rather, the network ``turtles up.'' It displays a
propensity for higher clustering, strong tie
interaction, and an intensification of insider vs.
outsider and within-role vs. between-role
communication. Further, we find changes in network
structure predict shifts in cognitive and affective
processes, execution of new transactions, and local
optimality of transactions better than prices,
revealing the important predictive relationship between
network structure and collective behavior within a
social network.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Gilani:2019:LSB,
author = "Zafar Gilani and Reza Farahbakhsh and Gareth Tyson and
Jon Crowcroft",
title = "A Large-scale Behavioural Analysis of Bots and Humans
on {Twitter}",
journal = j-TWEB,
volume = "13",
number = "1",
pages = "7:1--7:??",
month = feb,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3298789",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:06 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Recent research has shown a substantial active
presence of bots in online social networks (OSNs). In
this article, we perform a comparative analysis of the
usage and impact of bots and humans on Twitter-one of
the largest OSNs in the world. We collect a large-scale
Twitter dataset and define various metrics based on
tweet metadata. Using a human annotation task, we
assign ``bot'' and ``human'' ground-truth labels to the
dataset and compare the annotations against an online
bot detection tool for evaluation. We then ask a series
of questions to discern important behavioural
characteristics of bots and humans using metrics within
and among four popularity groups. From the comparative
analysis, we draw clear differences and interesting
similarities between the two entities.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Thoma:2019:FEC,
author = "Steffen Thoma and Andreas Thalhammer and Andreas Harth
and Rudi Studer",
title = "{FusE}: Entity-Centric Data Fusion on Linked Data",
journal = j-TWEB,
volume = "13",
number = "2",
pages = "8:1--8:??",
month = apr,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3306128",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3306128",
abstract = "Many current web pages include structured data which
can directly be processed and used. Search engines, in
particular, gather that structured data and provide
question answering capabilities over the integrated
data with an entity-centric presentation of the
results. Due to the decentralized nature of the web,
multiple structured data sources can provide similar
information about an entity. But data from different
sources may involve different vocabularies and modeling
granularities, which makes integration difficult. We
present FusE, an approach that identifies similar
entity-specific data across sources, independent of the
vocabulary and data modeling choices. We apply our
method along the scenario of a trustable knowledge
panel, conduct experiments in which we identify and
process entity data from web sources, and compare the
output to a competing system. The results underline the
advantages of the presented entity-centric data fusion
approach.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Alarte:2019:WWT,
author = "Juli{\'a}n Alarte and Josep Silva and Salvador
Tamarit",
title = "What {Web} Template Extractor Should {I} Use? {A}
Benchmarking and Comparison for Five Template
Extractors",
journal = j-TWEB,
volume = "13",
number = "2",
pages = "9:1--9:??",
month = apr,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3316810",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3316810",
abstract = "A Web template is a resource that implements the
structure and format of a website, making it ready for
plugging content into already formatted and prepared
pages. For this reason, templates are one of the main
development resources for website engineers, because
they increase productivity. Templates are also useful
for the final user, because they provide uniformity and
a common look and feel for all webpages. However, from
the point of view of crawlers and indexers, templates
are an important problem, because templates usually
contain irrelevant information, such as advertisements,
menus, and banners. Processing and storing this
information leads to a waste of resources (storage
space, bandwidth, etc.). It has been measured that
templates represent between 40\% and 50\% of data on
the Web. Therefore, identifying templates is essential
for indexing tasks. There exist many techniques and
tools for template extraction, but, unfortunately, it
is not clear at all which template extractor should a
user/system use, because they have never been compared,
and because they present different (complementary)
features such as precision, recall, and efficiency. In
this work, we compare the most advanced template
extractors. We implemented and evaluated five of the
most advanced template extractors in the literature. To
compare all of them, we implemented a workbench, where
they have been integrated and evaluated. Thanks to this
workbench, we can provide a fair empirical comparison
of all methods using the same benchmarks, technology,
implementation language, and evaluation criteria.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Vicario:2019:PFN,
author = "Michela {Del Vicario} and Walter Quattrociocchi and
Antonio Scala and Fabiana Zollo",
title = "Polarization and Fake News: Early Warning of Potential
Misinformation Targets",
journal = j-TWEB,
volume = "13",
number = "2",
pages = "10:1--10:??",
month = apr,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3316809",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3316809",
abstract = "Users' polarization and confirmation bias play a key
role in misinformation spreading on online social
media. Our aim is to use this information to determine
in advance potential targets for hoaxes and fake news.
In this article, we introduce a framework for promptly
identifying polarizing content on social media and,
thus, ``predicting'' future fake news topics. We
validate the performances of the proposed methodology
on a massive Italian Facebook dataset, showing that we
are able to identify topics that are susceptible to
misinformation with 77\% accuracy. Moreover, such
information may be embedded as a new feature in an
additional classifier able to recognize fake news with
91\% accuracy. The novelty of our approach consists in
taking into account a series of characteristics related
to users' behavior on online social media such as
Facebook, making a first, important step towards the
mitigation of misinformation phenomena by supporting
the identification of potential misinformation targets
and thus the design of tailored counter-narratives.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Cresci:2019:CPU,
author = "Stefano Cresci and Fabrizio Lillo and Daniele Regoli
and Serena Tardelli and Maurizio Tesconi",
title = "Cashtag Piggybacking: Uncovering Spam and Bot Activity
in Stock Microblogs on {Twitter}",
journal = j-TWEB,
volume = "13",
number = "2",
pages = "11:1--11:??",
month = apr,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3313184",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3313184",
abstract = "Microblogs are increasingly exploited for predicting
prices and traded volumes of stocks in financial
markets. However, it has been demonstrated that much of
the content shared in microblogging platforms is
created and publicized by bots and spammers. Yet, the
presence (or lack thereof) and the impact of fake stock
microblogs has never been systematically investigated
before. Here, we study 9M tweets related to stocks of
the five main financial markets in the US. By comparing
tweets with financial data from Google Finance, we
highlight important characteristics of Twitter stock
microblogs. More importantly, we uncover a malicious
practice-referred to as cashtag piggybacking
-perpetrated by coordinated groups of bots and likely
aimed at promoting low-value stocks by exploiting the
popularity of high-value ones. Among the findings of
our study is that as much as 71\% of the authors of
suspicious financial tweets are classified as bots by a
state-of-the-art spambot-detection algorithm.
Furthermore, 37\% of them were suspended by Twitter a
few months after our investigation. Our results call
for the adoption of spam- and bot-detection techniques
in all studies and applications that exploit
user-generated content for predicting the stock
market.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Watanabe:2019:LCP,
author = "Willian Massami Watanabe and Giovana L{\'a}zaro
Am{\^e}ndola and Fagner Christian Paes",
title = "Layout Cross-Platform and Cross-Browser
Incompatibilities Detection using Classification of
{DOM} Elements",
journal = j-TWEB,
volume = "13",
number = "2",
pages = "12:1--12:??",
month = apr,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3316808",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3316808",
abstract = "Web applications can be accessed through a variety of
user agent configurations, in which the browser,
platform, and device capabilities are not under the
control of developers. In order to grant the
compatibility of a web application in each environment,
developers must manually inspect their web application
in a wide variety of devices, platforms, and browsers.
Web applications can be rendered inconsistently
depending on the browser, the platform, and the device
capabilities which are used. Furthermore, the devices'
different viewport widths impact the way web
applications are rendered in them, in which elements
can be resized and change their absolute positions in
the display. These adaptation strategies must also be
considered in automatic incompatibility detection
approaches in the state of the art. Hence, we propose a
classification approach for detecting Layout
Cross-platform and Cross-browser incompatibilities,
which considers the adaptation strategies used in
responsive web applications. Our approach is an
extension of previous Cross-browser incompatibility
detection approaches and has the goal of reducing the
cost associated with manual inspections in different
devices, platforms, and browsers, by automatically
detecting Layout incompatibilities in this scenario.
The proposed approach classifies each DOM element which
composes a web application as an incompatibility or
not, based on its attributes, position, alignment,
screenshot, and the viewport width of the browser. We
report the results of an experiment conducted with 42
Responsive Web Applications, rendered in three devices
(Apple iPhone SE, Apple iPhone 8 Plus, and Motorola
Moto G4) and browsers (Google Chrome and Apple Safari).
The results (with F-measure of 0.70) showed evidence
which quantify the effectiveness of our classification
approach, and it could be further enhanced for
detecting Cross-platform and Cross-browser
incompatibilities. Furthermore, in the experiment, our
approach also performed better when compared to a
former state-of-the-art classification technique for
Cross-browser incompatibilities detection.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Sigg:2019:EUP,
author = "Stephan Sigg and Eemil Lagerspetz and Ella Peltonen
and Petteri Nurmi and Sasu Tarkoma",
title = "Exploiting Usage to Predict Instantaneous App
Popularity: Trend Filters and Retention Rates",
journal = j-TWEB,
volume = "13",
number = "2",
pages = "13:1--13:??",
month = apr,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3199677",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3199677",
abstract = "Popularity of mobile apps is traditionally measured by
metrics such as the number of downloads, installations,
or user ratings. A problem with these measures is that
they reflect usage only indirectly. Indeed, retention
rates, i.e., the number of days users continue to
interact with an installed app, have been suggested to
predict successful app lifecycles. We conduct the first
independent and large-scale study of retention rates
and usage trends on a dataset of app-usage data from a
community of 339,842 users and more than 213,667 apps.
Our analysis shows that, on average, applications lose
65\% of their users in the first week, while very
popular applications (top 100) lose only 35\%. It also
reveals, however, that many applications have more
complex usage behaviour patterns due to seasonality,
marketing, or other factors. To capture such effects,
we develop a novel app-usage trend measure which
provides instantaneous information about the popularity
of an application. Analysis of our data using this
trend filter shows that roughly 40\% of all apps never
gain more than a handful of users ( Marginal apps).
Less than 0.1\% of the remaining 60\% are constantly
popular ( Dominant apps), 1\% have a quick drain of
usage after an initial steep rise ( Expired apps), and
6\% continuously rise in popularity ( Hot apps). From
these, we can distinguish, for instance, trendsetters
from copycat apps. We conclude by demonstrating that
usage behaviour trend information can be used to
develop better mobile app recommendations.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Alorainy:2019:EAU,
author = "Wafa Alorainy and Pete Burnap and Han Liu and Matthew
L. Williams",
title = "{``The Enemy Among Us''}: Detecting Cyber Hate Speech
with Threats-based Othering Language Embeddings",
journal = j-TWEB,
volume = "13",
number = "3",
pages = "14:1--14:??",
month = oct,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3324997",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3324997",
abstract = "Offensive or antagonistic language targeted at
individuals and social groups based on their personal
characteristics (also known as cyber hate speech or
cyberhate) has been frequently posted and widely
circulated via the World Wide Web. This can be
considered as a key risk factor for individual and
societal tension surrounding regional instability.
Automated Web-based cyberhate detection is important
for observing and understanding community and regional
societal tension-especially in online social networks
where posts can be rapidly and widely viewed and
disseminated. While previous work has involved using
lexicons, bags-of-words, or probabilistic language
parsing approaches, they often suffer from a similar
issue, which is that cyberhate can be subtle and
indirect-thus, depending on the occurrence of
individual words or phrases, can lead to a significant
number of false negatives, providing inaccurate
representation of the trends in cyberhate. This problem
motivated us to challenge thinking around the
representation of subtle language use, such as
references to perceived threats from ``the other''
including immigration or job prosperity in a hateful
context. We propose a novel ``othering'' feature set
that utilizes language use around the concept of
``othering'' and intergroup threat theory to identify
these subtleties, and we implement a wide range of
classification methods using embedding learning to
compute semantic distances between parts of speech
considered to be part of an ``othering'' narrative. To
validate our approach, we conducted two sets of
experiments. The first involved comparing the results
of our novel method with state-of-the-art baseline
models from the literature. Our approach outperformed
all existing methods. The second tested the best
performing models from the first phase on unseen
datasets for different types of cyberhate, namely
religion, disability, race, and sexual orientation. The
results showed F-measure scores for classifying hateful
instances obtained through applying our model of 0.81,
0.71, 0.89, and 0.72, respectively, demonstrating the
ability of the ``othering'' narrative to be an
important part of model generalization.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Zhao:2019:USE,
author = "Liping Zhao and Pericles Loucopoulos and Evangelia
Kavakli and Keletso J. Letsholo",
title = "User Studies on End-User Service Composition: a
Literature Review and a Design Framework",
journal = j-TWEB,
volume = "13",
number = "3",
pages = "15:1--15:??",
month = oct,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3340294",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3340294",
abstract = "Context: End-user service composition (EUSC) is a
service-oriented paradigm that aims to empower end
users and allow them to compose their own web
applications from reusable service components. User
studies have been used to evaluate EUSC tools and
processes. Such an approach should benefit software
development, because incorporating end users' feedback
into software development should make software more
useful and usable. Problem: There is a gap in our
understanding of what constitutes a user study and how
a good user study should be designed, conducted, and
reported. Goal: This article aims to address this gap.
Method: The article presents a systematic review of 47
selected user studies for EUSC. Guided by a review
framework, the article systematically and consistently
assesses the focus, methodology and cohesion of each of
these studies. Results: The article concludes that the
focus of these studies is clear, but their methodology
is incomplete and inadequate, their overall cohesion is
poor. The findings lead to the development of a design
framework and a set of questions for the design,
reporting, and review of good user studies for EUSC.
The detailed analysis and the insights obtained from
the analysis should be applicable to the design of user
studies for service-oriented systems as well and indeed
for any user studies related to software artifacts.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Chatzakou:2019:DCC,
author = "Despoina Chatzakou and Ilias Leontiadis and Jeremy
Blackburn and Emiliano {De Cristofaro} and Gianluca
Stringhini and Athena Vakali and Nicolas Kourtellis",
title = "Detecting Cyberbullying and Cyberaggression in Social
Media",
journal = j-TWEB,
volume = "13",
number = "3",
pages = "17:1--17:??",
month = oct,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3343484",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Oct 22 08:10:07 MDT 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3343484",
abstract = "Cyberbullying and cyberaggression are increasingly
worrisome phenomena affecting people across all
demographics. More than half of young social media
users worldwide have been exposed to such prolonged
and/or coordinated digital harassment. Victims can
experience a wide range of emotions, with negative
consequences such as embarrassment, depression,
isolation from other community members, which embed the
risk to lead to even more critical consequences, such
as suicide attempts. In this work, we take the first
concrete steps to understand the characteristics of
abusive behavior in Twitter, one of today's largest
social media platforms. We analyze 1.2 million users
and 2.1 million tweets, comparing users participating
in discussions around seemingly normal topics like the
NBA, to those more likely to be hate-related, such as
the Gamergate controversy, or the gender pay inequality
at the BBC station. We also explore specific
manifestations of abusive behavior, i.e., cyberbullying
and cyberaggression, in one of the hate-related
communities (Gamergate). We present a robust
methodology to distinguish bullies and aggressors from
normal Twitter users by considering text, user, and
network-based attributes. Using various
state-of-the-art machine-learning algorithms, we
classify these accounts with over 90\% accuracy and
AUC. Finally, we discuss the current status of Twitter
user accounts marked as abusive by our methodology and
study the performance of potential mechanisms that can
be used by Twitter to suspend users in the future.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Perino:2019:LTM,
author = "Diego Perino and Matteo Varvello and Claudio
Soriente",
title = "Long-term Measurement and Analysis of the Free Proxy
Ecosystem",
journal = j-TWEB,
volume = "13",
number = "4",
pages = "18:1--18:??",
month = dec,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3360695",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Dec 21 07:39:03 MST 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3360695",
abstract = "Free web proxies promise anonymity and censorship
circumvention at no cost. Several websites publish
lists of free proxies organized by country, anonymity
level, and performance. These lists index hundreds of
thousands of hosts discovered via automated tools and
crowd-sourcing. A complex free proxy ecosystem has been
forming over the years, of which very little is known.
In this article, we shed light on this ecosystem via a
distributed measurement platform that leverages both
active and passive measurements. Active measurements
are carried out by an infrastructure we name
ProxyTorrent, which discovers free proxies, assesses
their performance, and detects potential malicious
activities. Passive measurements focus on proxy
performance and usage in the wild, and are accomplished
by means of a Chrome extension named Ciao. ProxyTorrent
has been running since January 2017, monitoring up to
230K free proxies. Ciao was launched in March 2017 and
has thus far served roughly 9.7K users and generated
14TB of traffic. Our analysis shows that less than 2\%
of the proxies announced on the Web indeed proxy
traffic on behalf of users; further, only half of these
proxies have decent performance and can be used
reliably. Every day, around 5\%--10\% of the active
proxies exhibit malicious behaviors, e.g.,
advertisement injection, TLS interception, and
cryptojacking, and these proxies are also the ones
providing the best performance. Through the analysis of
more than 14TB of proxied traffic, we show that web
browsing is the primary user activity. Geo-blocking
avoidance-allegedly a popular use case for free web
proxies-accounts for 30\% or less of the traffic, and
it mostly involves countries hosting popular
geo-blocked content.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Liu:2019:FPS,
author = "Daxin Liu and Gong Cheng and Qingxia Liu and Yuzhong
Qu",
title = "Fast and Practical Snippet Generation for {RDF}
Datasets",
journal = j-TWEB,
volume = "13",
number = "4",
pages = "19:1--19:??",
month = dec,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3365575",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Dec 21 07:39:03 MST 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3365575",
abstract = "Triple-structured open data creates value in many
ways. However, the reuse of datasets is still
challenging. Users feel difficult to assess the
usefulness of a large dataset containing thousands or
millions of triples. To satisfy the needs, existing
abstractive methods produce a concise high-level
abstraction of data. Complementary to that, we adopt
the extractive strategy and aim to select the optimum
small subset of data from a dataset as a snippet to
compactly illustrate the content of the dataset. This
has been formulated as a combinatorial optimization
problem in our previous work. In this article, we
design a new algorithm for the problem, which is an
order of magnitude faster than the previous one but has
the same approximation ratio. We also develop an
anytime algorithm that can generate empirically better
solutions using additional time. To suit datasets that
are partially accessible via online query services
(e.g., SPARQL endpoints for RDF data), we adapt our
algorithms to trade off quality of snippet for
feasibility and efficiency in the Web environment. We
carry out extensive experiments based on real RDF
datasets and SPARQL endpoints for evaluating quality
and running time. The results demonstrate the
effectiveness and practicality of our proposed
algorithms.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Manica:2019:CUH,
author = "Edimar Manica and Carina Friedrich Dorneles and Renata
Galante",
title = "Combining {URL} and {HTML} Features for Entity
Discovery in the {Web}",
journal = j-TWEB,
volume = "13",
number = "4",
pages = "20:1--20:??",
month = dec,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3365574",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Dec 21 07:39:03 MST 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/ft_gateway.cfm?id=3365574",
abstract = "The web is a large repository of entity-pages. An
entity-page is a page that publishes data representing
an entity of a particular type, for example, a page
that describes a driver on a website about a car racing
championship. The attribute values published in the
entity-pages can be used for many data-driven
companies, such as insurers, retailers, and search
engines. In this article, we define a novel method,
called SSUP, which discovers the entity-pages on the
websites. The novelty of our method is that it combines
URL and HTML features in a way that allows the URL
terms to have different weights depending on their
capacity to distinguish entity-pages from other pages,
and thus the efficacy of the entity-page discovery task
is increased. SSUP determines the similarity thresholds
on each website without human intervention. We carried
out experiments on a dataset with different real-world
websites and a wide range of entity types. SSUP
achieved a 95\% rate of precision and 85\% recall rate.
Our method was compared with two state-of-the-art
methods and outperformed them with a precision gain
between 51\% and 66\%.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Yu:2019:EPP,
author = "Weiren Yu and Julie McCann and Chengyuan Zhang",
title = "Efficient Pairwise Penetrating-rank Similarity
Retrieval",
journal = j-TWEB,
volume = "13",
number = "4",
pages = "21:1--21:??",
month = dec,
year = "2019",
CODEN = "????",
DOI = "https://doi.org/10.1145/3368616",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Dec 21 07:39:03 MST 2019",
bibsource = "http://www.math.utah.edu/pub/tex/bib/pagerank.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
abstract = "Many web applications demand a measure of similarity
between two entities, such as collaborative filtering,
web document ranking, linkage prediction, and anomaly
detection. P-Rank (Penetrating-Rank) has been accepted
as a promising graph-based similarity measure, as it
provides a comprehensive way of encoding both incoming
and outgoing links into assessment. However, the
existing method to compute P-Rank is iterative in
nature and rather cost-inhibitive. Moreover, the
accuracy estimate and stability issues for P-Rank
computation have not been addressed. In this article,
we consider the optimization techniques for P-Rank
search that encompasses its accuracy, stability, and
computational efficiency. (1) The accuracy estimation
is provided for P-Rank iterations, with the aim to find
out the number of iterations, $k$, required to
guarantee a desired accuracy. (2) A rigorous bound on
the condition number of P-Rank is obtained for
stability analysis. Based on this bound, it can be
shown that P-Rank is stable and well-conditioned when
the damping factors are chosen to be suitably small.
(3) Two matrix-based algorithms, applicable to digraphs
and undirected graphs, are, respectively, devised for
efficient P-Rank computation, which improves the
computational time from $ O(k n^3) $ to $ O(\upsilon
n^2 + \upsilon^6) $ for digraphs, and to $ O(\upsilon
n^2) $ for undirected graphs, where $n$ is the number
of vertices in the graph, and $ \upsilon (\ll n)$ is
the target rank of the graph. Moreover, our proposed
algorithms can significantly reduce the memory space of
P-Rank computations from $ O(n^2) $ to $ O(\upsilon n +
\upsilon^4) $ for digraphs, and to $ O(\upsilon n) $
for undirected graphs, respectively. Finally, extensive
experiments on real-world and synthetic datasets
demonstrate the usefulness and efficiency of the
proposed techniques for P-Rank similarity assessment on
various networks.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}
@Article{Eraslan:2020:BBW,
author = "Sukru Eraslan and Yeliz Yesilada and Simon Harper",
title = "{``The Best of Both Worlds!''}: Integration of {Web}
Page and Eye Tracking Data Driven Approaches for
Automatic {AOI} Detection",
journal = j-TWEB,
volume = "14",
number = "1",
pages = "1:1--1:31",
month = feb,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3372497",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Feb 8 06:24:56 MST 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3372497",
abstract = "Web pages are composed of different kinds of elements
(menus, adverts, etc.). Segmenting pages into their
elements has long been important in understanding how
people experience those pages and in making those
experiences {``better.''} Many approaches have
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Shah:2020:OMA,
author = "Ankit Shah and Rajesh Ganesan and Sushil Jajodia and
Hasan Cam",
title = "An Outsourcing Model for Alert Analysis in a
Cybersecurity Operations Center",
journal = j-TWEB,
volume = "14",
number = "1",
pages = "2:1--2:22",
month = feb,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3372498",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Feb 8 06:24:56 MST 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3372498",
abstract = "A typical Cybersecurity Operations Center (CSOC) is a
service organization. It hires and trains analysts,
whose task is to perform analysis of alerts that were
generated while monitoring the client's networks. Due
to ever-increasing financial and \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Abulaish:2020:SFL,
author = "Muhammad Abulaish and Ashraf Kamal and Mohammed J.
Zaki",
title = "A Survey of Figurative Language and Its Computational
Detection in Online Social Networks",
journal = j-TWEB,
volume = "14",
number = "1",
pages = "3:1--3:52",
month = feb,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3375547",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Feb 8 06:24:56 MST 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3375547",
abstract = "The frequent usage of figurative language on online
social networks, especially on Twitter, has the
potential to mislead traditional sentiment analysis and
recommender systems. Due to the extensive use of
slangs, bashes, flames, and non-literal texts,
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Hassanpour:2020:IAV,
author = "Masoud Hassanpour and Seyed Amir Hoseinitabatabaei and
Payam Barnaghi and Rahim Tafazolli",
title = "Improving the Accuracy of the Video Popularity
Prediction Models through User Grouping and Video
Popularity Classification",
journal = j-TWEB,
volume = "14",
number = "1",
pages = "4:1--4:28",
month = feb,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3372499",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Feb 8 06:24:56 MST 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3372499",
abstract = "This article proposes a novel approach for enhancing
the video popularity prediction models. Using the
proposed approach, we enhance three popularity
prediction techniques that outperform the accuracy of
the prior state-of-the-art solutions. The major
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Li:2020:TAS,
author = "Guohui Li and Qi Chen and Bolong Zheng and Nguyen Quoc
Viet Hung and Pan Zhou and Guanfeng Liu",
title = "Time-aspect-sentiment Recommendation Models Based on
Novel Similarity Measure Methods",
journal = j-TWEB,
volume = "14",
number = "2",
pages = "5:1--5:26",
month = apr,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3375548",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 21 08:25:53 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3375548",
abstract = "The explosive growth of e-commerce has led to the
development of the recommendation system. The
recommendation system aims to provide a set of items
that meet users' personalized needs through analyzing
users' consumption records. However, the \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Carpineto:2020:ESA,
author = "Claudio Carpineto and Giovanni Romano",
title = "An Experimental Study of Automatic Detection and
Measurement of Counterfeit in Brand Search Results",
journal = j-TWEB,
volume = "14",
number = "2",
pages = "6:1--6:35",
month = apr,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3378443",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 21 08:25:53 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3378443",
abstract = "Brand search results are poisoned by fake ecommerce
websites that infringe on the trademark rights of
legitimate holders. In this article, we study how to
tackle and measure this problem automatically. We
present a pipeline with two machine learning \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Tonge:2020:IPP,
author = "Ashwini Tonge and Cornelia Caragea",
title = "Image Privacy Prediction Using Deep Neural Networks",
journal = j-TWEB,
volume = "14",
number = "2",
pages = "7:1--7:32",
month = apr,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3386082",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 21 08:25:53 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3386082",
abstract = "Images today are increasingly shared online on social
networking sites such as Facebook, Flickr, and
Instagram. Image sharing occurs not only within a group
of friends but also more and more outside a user's
social circles for purposes of social \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Laperdrix:2020:BFS,
author = "Pierre Laperdrix and Nataliia Bielova and Benoit
Baudry and Gildas Avoine",
title = "Browser Fingerprinting: a Survey",
journal = j-TWEB,
volume = "14",
number = "2",
pages = "8:1--8:33",
month = apr,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3386040",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 21 08:25:53 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3386040",
abstract = "With this article, we survey the research performed in
the domain of browser fingerprinting, while providing
an accessible entry point to newcomers in the field. We
explain how this technique works and where it stems
from. We analyze the related work in \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Shi:2020:TAW,
author = "Min Shi and Yufei Tang and Xingquan Zhu and Jianxun
Liu",
title = "Topic-aware {Web} Service Representation Learning",
journal = j-TWEB,
volume = "14",
number = "2",
pages = "9:1--9:23",
month = apr,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3386041",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Apr 21 08:25:53 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3386041",
abstract = "The advent of Service-Oriented Architecture (SOA) has
brought a fundamental shift in the way in which
distributed applications are implemented. An
overwhelming number of Web-based services (e.g., APIs
and Mashups) have leveraged this shift and furthered
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Xiao:2020:PRF,
author = "Zhijun Xiao and Cuiping Li and Hong Chen",
title = "{PatternRank+NN}: a Ranking Framework Bringing User
Behaviors into Entity Set Expansion from {Web} Search
Queries",
journal = j-TWEB,
volume = "14",
number = "3",
pages = "10:1--10:15",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3386042",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 22 17:29:55 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/pagerank.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3386042",
abstract = "We propose a ranking framework, called PatternRank+NN,
for expanding a set of seed entities of a particular
class (i.e., entity set expansion) from Web search
queries. PatternRank+NN consists of two parts:
PatternRank and NN. Unlike the traditional \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wu:2020:STI,
author = "Huijun Wu and Chen Wang and Richard Nock and Wei Wang
and Jie Yin and Kai Lu and Liming Zhu",
title = "{SMINT}: Toward Interpretable and Robust Model Sharing
for Deep Neural Networks",
journal = j-TWEB,
volume = "14",
number = "3",
pages = "11:1--11:28",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3381833",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 22 17:29:55 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3381833",
abstract = "Sharing a pre-trained machine learning model,
particularly a deep neural network via prediction APIs,
is becoming a common practice on machine learning as a
service (MLaaS) platforms nowadays. Although deep
neural networks (DNN) have shown remarkable \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Chattopadhyay:2020:QAA,
author = "Soumi Chattopadhyay and Ansuman Banerjee",
title = "{QoS}-aware Automatic {Web} Service Composition with
Multiple Objectives",
journal = j-TWEB,
volume = "14",
number = "3",
pages = "12:1--12:38",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3389147",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 22 17:29:55 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3389147",
abstract = "Automatic web service composition has received a
significant research attention in service-oriented
computing over decades of research. With increasing
number of web services, providing an end-to-end Quality
of Service (QoS) guarantee in responding to \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wu:2020:SAR,
author = "Zhiang Wu and Changsheng Li and Jie Cao and Yong Ge",
title = "On Scalability of Association-rule-based
Recommendation: a Unified Distributed-computing
Framework",
journal = j-TWEB,
volume = "14",
number = "3",
pages = "13:1--13:21",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3398202",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 22 17:29:55 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3398202",
abstract = "The association-rule-based approach is one of the most
common technologies for building recommender systems
and it has been extensively adopted for commercial use.
A variety of techniques, mainly including eligible rule
selection and multiple rules \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Ma:2020:RTC,
author = "Yun Ma and Ziniu Hu and Diandian Gu and Li Zhou and
Qiaozhu Mei and Gang Huang and Xuanzhe Liu",
title = "Roaming Through the Castle Tunnels: an Empirical
Analysis of Inter-app Navigation of {Android} Apps",
journal = j-TWEB,
volume = "14",
number = "3",
pages = "14:1--14:24",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3395050",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Jul 22 17:29:55 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3395050",
abstract = "Smartphone applications (a.k.a., apps) have become
indispensable in our everyday life and work. In
practice, accomplishing a task on smartphones may
require the user to navigate among various apps. Unlike
Web pages that are inherently interconnected \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Jeong:2020:DOW,
author = "Hyuk-Jin Jeong and Inchang Jeong and Soo-Mook Moon",
title = "Dynamic Offloading of {Web} Application Execution
Using Snapshot",
journal = j-TWEB,
volume = "14",
number = "4",
pages = "15:1--15:24",
month = sep,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3402124",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Sep 5 18:55:05 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3402124",
abstract = "Mobile web platforms are facing new demands for
emerging applications, such as machine learning or
augmented reality, which require significant computing
powers beyond that of current mobile hardware.
Computation offloading can accelerate these apps by
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Javed:2020:EBD,
author = "Amir Javed and Pete Burnap and Matthew L. Williams and
Omer F. Rana",
title = "Emotions Behind Drive-by Download Propagation on
{Twitter}",
journal = j-TWEB,
volume = "14",
number = "4",
pages = "16:1--16:26",
month = sep,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3408894",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Sep 5 18:55:05 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3408894",
abstract = "Twitter has emerged as one of the most popular
platforms to get updates on entertainment and current
events. However, due to its 280-character restriction
and automatic shortening of URLs, it is continuously
targeted by cybercriminals to carry out drive-.
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Mittos:2020:AGT,
author = "Alexandros Mittos and Savvas Zannettou and Jeremy
Blackburn and Emiliano {De Cristofaro}",
title = "Analyzing Genetic Testing Discourse on the {Web}
Through the Lens of {Twitter}, {Reddit}, and {4chan}",
journal = j-TWEB,
volume = "14",
number = "4",
pages = "17:1--17:38",
month = sep,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3404994",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Sep 5 18:55:05 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3404994",
abstract = "Recent progress in genomics has enabled the emergence
of a flourishing market for direct-to-consumer (DTC)
genetic testing. Companies like 23andMe and AncestryDNA
provide affordable health, genealogy, and ancestry
reports, and have already tested tens \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zubiaga:2020:EDS,
author = "Arkaitz Zubiaga and Aiqi Jiang",
title = "Early Detection of Social Media Hoaxes at Scale",
journal = j-TWEB,
volume = "14",
number = "4",
pages = "18:1--18:23",
month = sep,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3407194",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Sep 5 18:55:05 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3407194",
abstract = "The unmoderated nature of social media enables the
diffusion of hoaxes, which in turn jeopardises the
credibility of information gathered from social media
platforms. Existing research on automated detection of
hoaxes has the limitation of using \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Mazumdar:2020:CSP,
author = "Pramit Mazumdar and Bidyut Kr. Patra and Korra Sathya
Babu",
title = "Cold-start Point-of-interest Recommendation through
Crowdsourcing",
journal = j-TWEB,
volume = "14",
number = "4",
pages = "19:1--19:36",
month = sep,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3407182",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Sep 5 18:55:05 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3407182",
abstract = "Recommender system is a popular tool that aims to
provide personalized suggestions to user about items,
products, services, and so on. Recommender system has
effectively been used in online social networks,
especially the location-based social networks
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Cao:2021:CCB,
author = "Jian Cao and Tingjie Jia and Shiyou Qian and Haiyan
Zhao and Jie Wang",
title = "{CBPCS}: a Cache-block-based Service Process Caching
Strategy to Accelerate the Execution of Service
Processes",
journal = j-TWEB,
volume = "15",
number = "1",
pages = "1:1--1:29",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3411494",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3411494",
abstract = "With the development of cloud computing and the advent
of the Web 2.0 era, composing a set of Web services as
a service process is becoming a common practice to
provide more functional services. However, a service
process involves multiple service \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Vidyapu:2021:IMW,
author = "Sandeep Vidyapu and Vijaya Saradhi Vedula and Samit
Bhattacharya",
title = "Investigating and Modeling the {Web} Elements' Visual
Feature Influence on Free-viewing Attention",
journal = j-TWEB,
volume = "15",
number = "1",
pages = "2:1--2:27",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3409474",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3409474",
abstract = "User attentional analyses on web elements help in
synthesis and rendering of webpages. However, majority
of the existing analyses are limited in incorporating
the intrinsic visual features of text and images. This
study aimed to analyze the influence of \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Chen:2021:DVE,
author = "Xu Chen and Jiangchao Yao and Maosen Li and Ya Zhang
and Yanfeng Wang",
title = "Decoupled Variational Embedding for Signed Directed
Networks",
journal = j-TWEB,
volume = "15",
number = "1",
pages = "3:1--3:31",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3408298",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3408298",
abstract = "Node representation learning for signed directed
networks has received considerable attention in many
real-world applications such as link sign prediction,
node classification, and node recommendation. The
challenge lies in how to adequately encode the
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2021:ACN,
author = "Wei Wang and Jiaying Liu and Tao Tang and Suppawong
Tuarob and Feng Xia and Zhiguo Gong and Irwin King",
title = "Attributed Collaboration Network Embedding for
Academic Relationship Mining",
journal = j-TWEB,
volume = "15",
number = "1",
pages = "4:1--4:20",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3409736",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3409736",
abstract = "Finding both efficient and effective quantitative
representations for scholars in scientific digital
libraries has been a focal point of research. The
unprecedented amounts of scholarly datasets, combined
with contemporary machine learning and big data
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Bailey:2021:SLA,
author = "Shawn Bailey and Yue Zhang and Arti Ramesh and
Jennifer Golbeck and Lise Getoor",
title = "A Structured and Linguistic Approach to Understanding
Recovery and Relapse in {AA}",
journal = j-TWEB,
volume = "15",
number = "1",
pages = "5:1--5:35",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3423208",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3423208",
abstract = "Alcoholism, also known as Alcohol Use Disorder (AUD),
is a serious problem affecting millions of people
worldwide. Recovery from AUD is known to be challenging
and often leads to relapse at various points after
enrolling in a rehabilitation program such \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Gong:2021:CSP,
author = "Qingyuan Gong and Yang Chen and Xinlei He and Yu Xiao
and Pan Hui and Xin Wang and Xiaoming Fu",
title = "Cross-site Prediction on Social Influence for
Cold-start Users in Online Social Networks",
journal = j-TWEB,
volume = "15",
number = "2",
pages = "6:1--6:23",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3409108",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3409108",
abstract = "Online social networks (OSNs) have become a commodity
in our daily life. As an important concept in sociology
and viral marketing, the study of social influence has
received a lot of attentions in academia. Most of the
existing proposals work well on \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Alhosban:2021:TPS,
author = "Amal Alhosban and Zaki Malik and Khayyam Hashmi and
Brahim Medjahed and Hassan Al-Ababneh",
title = "A Two Phases Self-healing Framework for
Service-oriented Systems",
journal = j-TWEB,
volume = "15",
number = "2",
pages = "7:1--7:25",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3450443",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3450443",
abstract = "Service-Oriented Architectures (SOA) enable the
automatic creation of business applications from
independently developed and deployed Web services. As
Web services are inherently a priori unknown, how to
deliver reliable Web services compositions is a
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Flores:2021:UWT,
author = "Marcel Flores and Andrew Kahn and Marc Warrior and
Alan Mislove and Aleksandar Kuzmanovic",
title = "Utilizing {Web} Trackers for {Sybil} Defense",
journal = j-TWEB,
volume = "15",
number = "2",
pages = "8:1--8:19",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3450444",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3450444",
abstract = "User tracking has become ubiquitous practice on the
Web, allowing services to recommend behaviorally
targeted content to users. In this article, we design
Alibi, a system that utilizes such readily available
personalized content, generated by \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Roy:2021:IAI,
author = "Soumyadeep Roy and Shamik Sural and Niyati Chhaya and
Anandhavelu Natarajan and Niloy Ganguly",
title = "An Integrated Approach for Improving Brand Consistency
of {Web} Content: Modeling, Analysis, and
Recommendation",
journal = j-TWEB,
volume = "15",
number = "2",
pages = "9:1--9:25",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3450445",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3450445",
abstract = "A consumer-dependent (business-to-consumer)
organization tends to present itself as possessing a
set of human qualities, which is termed the brand
personality of the company. The perception is impressed
upon the consumer through the content, be it in
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhang:2021:EWD,
author = "Jifeng Zhang and Wenjun Jiang and Jinrui Zhang and Jie
Wu and Guojun Wang",
title = "Exploring Weather Data to Predict Activity Attendance
in Event-based Social Network: From the Organizer's
View",
journal = j-TWEB,
volume = "15",
number = "2",
pages = "10:1--10:25",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3440134",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 22 08:52:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3440134",
abstract = "Event-based social networks (EBSNs) connect online and
offline lives. They allow online users with similar
interests to get together in real life. Attendance
prediction for activities in EBSNs has attracted a lot
of attention and several factors have \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{White:2021:WMN,
author = "Ryen W. White",
title = "Welcome Message from the New {Editor-in-Chief}",
journal = j-TWEB,
volume = "15",
number = "3",
pages = "11e:1--11e:1",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3456294",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3456294",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11e",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhang:2021:STR,
author = "Shuo Zhang and Krisztian Balog",
title = "Semantic Table Retrieval Using Keyword and Table
Queries",
journal = j-TWEB,
volume = "15",
number = "3",
pages = "11:1--11:33",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3441690",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3441690",
abstract = "Tables on the Web contain a vast amount of knowledge
in a structured form. To tap into this valuable
resource, we address the problem of table retrieval:
answering an information need with a ranked list of
tables. We investigate this problem in two \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Boschi:2021:WLW,
author = "Gioia Boschi and Anthony P. Young and Sagar Joglekar
and Chiara Cammarota and Nishanth Sastry",
title = "Who Has the Last Word? {Understanding} How to Sample
Online Discussions",
journal = j-TWEB,
volume = "15",
number = "3",
pages = "12:1--12:25",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3452936",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3452936",
abstract = "In online debates, as in offline ones, individual
utterances or arguments support or attack each other,
leading to some subset of arguments (potentially from
different sides of the debate) being considered more
relevant than others. However, online \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Jiang:2021:RSG,
author = "Wenjun Jiang and Jing Chen and Xiaofei Ding and Jie Wu
and Jiawei He and Guojun Wang",
title = "Review Summary Generation in Online Systems:
Frameworks for Supervised and Unsupervised Scenarios",
journal = j-TWEB,
volume = "15",
number = "3",
pages = "13:1--13:33",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3448015",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3448015",
abstract = "In online systems, including e-commerce platforms,
many users resort to the reviews or comments generated
by previous consumers for decision making, while their
time is limited to deal with many reviews. Therefore, a
review summary, which contains all \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Chelmis:2021:DIC,
author = "Charalampos Chelmis and Daphney-Stavroula Zois",
title = "Dynamic, Incremental, and Continuous Detection of
Cyberbullying in Online Social Media",
journal = j-TWEB,
volume = "15",
number = "3",
pages = "14:1--14:33",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3448014",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3448014",
abstract = "The potentially detrimental effects of cyberbullying
have led to the development of numerous automated,
data-driven approaches, with emphasis on classification
accuracy. Cyberbullying, as a form of abusive online
behavior, although not well-defined, is a \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Mistry:2021:SLB,
author = "Sajib Mistry and Sheik Mohammad Mostakim Fattah and
Athman Bouguettaya",
title = "Sequential Learning-based {IaaS} Composition",
journal = j-TWEB,
volume = "15",
number = "3",
pages = "15:1--15:37",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3452332",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:18 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3452332",
abstract = "We propose a novel Infrastructure-as-a-Service
composition framework that selects an optimal set of
consumer requests according to the provider's
qualitative preferences on long-term service
provisions. Decision variables are included in the
temporal \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhang:2021:SUC,
author = "Peng Zhang and Baoxi Liu and Xianghua Ding and Tun Lu
and Hansu Gu and Ning Gu",
title = "Studying and Understanding Characteristics of
Post-Syncing Practice and Goal in Social Network
Sites",
journal = j-TWEB,
volume = "15",
number = "4",
pages = "16:1--16:26",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3457986",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3457986",
abstract = "Many popular social network sites (SNSs) provide the
post-syncing functionality, which allows users to
synchronize posts automatically among different SNSs.
Nowadays there exists divergence on this functionality
from the view of sink SNS. The key to \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Parikh:2021:CSM,
author = "Pulkit Parikh and Harika Abburi and Niyati Chhaya and
Manish Gupta and Vasudeva Varma",
title = "Categorizing Sexism and Misogyny through Neural
Approaches",
journal = j-TWEB,
volume = "15",
number = "4",
pages = "17:1--17:31",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3457189",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3457189",
abstract = "Sexism, an injustice that subjects women and girls to
enormous suffering, manifests in blatant as well as
subtle ways. In the wake of growing documentation of
experiences of sexism on the web, the automatic
categorization of accounts of sexism has the \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Jiao:2021:SGM,
author = "Simiao Jiao and Zihui Xue and Xiaowei Chen and Yuedong
Xu",
title = "Sampling Graphlets of Multiplex Networks: a Restricted
Random Walk Approach",
journal = j-TWEB,
volume = "15",
number = "4",
pages = "18:1--18:31",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3456291",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3456291",
abstract = "Graphlets are induced subgraph patterns that are
crucial to the understanding of the structure and
function of a large network. A lot of effort has been
devoted to calculating graphlet statistics where random
walk-based approaches are commonly used to \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2021:IEA,
author = "Huan Wang and Chunming Qiao and Xuan Guo and Lei Fang
and Ying Sha and Zhiguo Gong",
title = "Identifying and Evaluating Anomalous Structural
Change-based Nodes in Generalized Dynamic Social
Networks",
journal = j-TWEB,
volume = "15",
number = "4",
pages = "19:1--19:22",
month = jul,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3457906",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Jul 15 07:11:19 MDT 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3457906",
abstract = "Recently, dynamic social network research has
attracted a great amount of attention, especially in
the area of anomaly analysis that analyzes the
anomalous change in the evolution of dynamic social
networks. However, most of the current research focused
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Liu:2022:FHU,
author = "Bang Liu and Hanlin Zhang and Linglong Kong and Di
Niu",
title = "Factorizing Historical User Actions for Next-Day
Purchase Prediction",
journal = j-TWEB,
volume = "16",
number = "1",
pages = "1:1--1:26",
month = feb,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3468227",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 7 08:00:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3468227",
abstract = "It is common practice for many large e-commerce
operators to analyze daily logged transaction data to
predict customer purchase behavior, which may
potentially lead to more effective recommendations and
increased sales. Traditional recommendation \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhao:2022:CAD,
author = "Yiji Zhao and Youfang Lin and Zhihao Wu and Yang Wang
and Haomin Wen",
title = "Context-aware Distance Measures for Dynamic Networks",
journal = j-TWEB,
volume = "16",
number = "1",
pages = "2:1--2:34",
month = feb,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3476228",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 7 08:00:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3476228",
abstract = "Dynamic networks are widely used in the social,
physical, and biological sciences as a concise
mathematical representation of the evolving
interactions in dynamic complex systems. Measuring
distances between network snapshots is important for
analyzing \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Crichton:2022:HDH,
author = "Kyle Crichton and Nicolas Christin and Lorrie Faith
Cranor",
title = "How Do Home Computer Users Browse the Web?",
journal = j-TWEB,
volume = "16",
number = "1",
pages = "3:1--3:27",
month = feb,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3473343",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 7 08:00:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3473343",
abstract = "With the ubiquity of web tracking, information on how
people navigate the internet is abundantly collected
yet, due to its proprietary nature, rarely distributed.
As a result, our understanding of user browsing
primarily derives from small-scale studies \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Andriamilanto:2022:LSE,
author = "Nampoina Andriamilanto and Tristan Allard and
Ga{\"e}tan {Le Guelvouit} and Alexandre Garel",
title = "A Large-scale Empirical Analysis of Browser
Fingerprints Properties for Web Authentication",
journal = j-TWEB,
volume = "16",
number = "1",
pages = "4:1--4:62",
month = feb,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3478026",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 7 08:00:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3478026",
abstract = "Modern browsers give access to several attributes that
can be collected to form a browser fingerprint.
Although browser fingerprints have primarily been
studied as a web tracking tool, they can contribute to
improve the current state of web security by \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Poiitis:2022:ADM,
author = "Marinos Poiitis and Athena Vakali and Nicolas
Kourtellis",
title = "On the Aggression Diffusion Modeling and Minimization
in {Twitter}",
journal = j-TWEB,
volume = "16",
number = "1",
pages = "5:1--5:24",
month = feb,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3486218",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Jan 7 08:00:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3486218",
abstract = "Aggression in online social networks has been studied
mostly from the perspective of machine learning, which
detects such behavior in a static context. However, the
way aggression diffuses in the network has received
little attention as it embeds modeling \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Nelson:2022:QCT,
author = "Michael Nelson and Sridhar Radhakrishnan and Chandra
Sekharan and Amlan Chatterjee and Sudhindra Gopal
Krishna",
title = "Queryable Compression on Time-evolving {Web} and
Social Networks with Streaming",
journal = j-TWEB,
volume = "16",
number = "2",
pages = "6:1--6:21",
month = may,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3495012",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 21 12:32:34 MDT 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3495012",
abstract = "Time-evolving web and social network graphs are
modeled as a set of pages/individuals (nodes) and their
arcs (links/relationships) that change over time. Due
to their popularity, they have become increasingly
massive in terms of their number of nodes, \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2022:LSE,
author = "Kai Wang and Jun Pang and Dingjie Chen and Yu Zhao and
Dapeng Huang and Chen Chen and Weili Han",
title = "A Large-scale Empirical Analysis of Ransomware
Activities in Bitcoin",
journal = j-TWEB,
volume = "16",
number = "2",
pages = "7:1--7:29",
month = may,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3494557",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 21 12:32:34 MDT 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3494557",
abstract = "Exploiting the anonymous mechanism of Bitcoin,
ransomware activities demanding ransom in bitcoins have
become rampant in recent years. Several existing
studies quantify the impact of ransomware activities,
mostly focusing on the amount of ransom. However,
victims' reactions in Bitcoin that can well reflect the
impact of ransomware activities are somehow largely
neglected. Besides, existing studies track ransom
transfers at the Bitcoin address level, making it
difficult for them to uncover the patterns of ransom
transfers from a macro perspective beyond Bitcoin
addresses.\par
In this article, we conduct a large-scale analysis of
ransom payments, ransom transfers, and victim
migrations in Bitcoin from 2012 to 2021. First, we
develop a fine-grained address clustering method to
cluster Bitcoin addresses into users, which enables us
to identify more addresses controlled by ransomware
criminals. Second, motivated by the fact that Bitcoin
activities and their participants already formed stable
industries, such as Darknet and Miner, we train a
multi-label classification model to identify the
industry identifiers of users. Third, we identify
ransom payment transactions and then quantify the
amount of ransom and the number of victims in 63
ransomware activities. Finally, after we analyze the
trajectories of ransom transferred across different
industries and track victims' migrations across
industries, we find out that to obscure the purposes of
their transfer trajectories, most ransomware criminals
(e.g., operators of Locky and Wannacry) prefer to
spread ransom into multiple industries instead of
utilizing the services of Bitcoin mixers. Compared with
other industries, Investment is highly resilient to
ransomware activities in the sense that the number of
users in Investment remains relatively stable.
Moreover, we also observe that a few victims become
active in the Darknet after paying ransom. Our findings
in this work can help authorities deeply understand
ransomware activities in Bitcoin. While our study
focuses on ransomware, our methods are potentially
applicable to other cybercriminal activities that have
similarly adopted bitcoins as their payments.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Biswas:2022:TFR,
author = "Arpita Biswas and Gourab K. Patro and Niloy Ganguly
and Krishna P. Gummadi and Abhijnan Chakraborty",
title = "Toward Fair Recommendation in Two-sided Platforms",
journal = j-TWEB,
volume = "16",
number = "2",
pages = "8:1--8:34",
month = may,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3503624",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 21 12:32:34 MDT 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3503624",
abstract = "Many online platforms today (such as Amazon, Netflix,
Spotify, LinkedIn, and AirBnB) can be thought of as
two-sided markets with producers and customers of goods
and services. Traditionally, recommendation services in
these platforms have focused on \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Magno:2022:MIO,
author = "Gabriel Magno and Virgilio Almeida",
title = "Measuring International Online Human Values with Word
Embeddings",
journal = j-TWEB,
volume = "16",
number = "2",
pages = "9:1--9:38",
month = may,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3501306",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 21 12:32:34 MDT 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3501306",
abstract = "As the Internet grows in number of users and in the
diversity of services, it becomes more influential on
peoples lives. It has the potential of constructing or
modifying the opinion, the mental perception, and the
values of individuals. What is being \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Karanatsiou:2022:MTB,
author = "Dimitra Karanatsiou and Pavlos Sermpezis and Dritjon
Gruda and Konstantinos Kafetsios and Ilias Dimitriadis
and Athena Vakali",
title = "My Tweets Bring All the Traits to the Yard: Predicting
Personality and Relational Traits in Online Social
Networks",
journal = j-TWEB,
volume = "16",
number = "2",
pages = "10:1--10:26",
month = may,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3523749",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat May 21 12:32:34 MDT 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3523749",
abstract = "Users in Online Social Networks (OSNs,) leave traces
that reflect their personality characteristics. The
study of these traces is important for several fields,
such as social science, psychology, marketing, and
others. Despite a marked increase in \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Qian:2022:PVR,
author = "Xin Qian and Ryan A. Rossi and Fan Du and Sungchul Kim
and Eunyee Koh and Sana Malik and Tak Yeon Lee and
Nesreen K. Ahmed",
title = "Personalized Visualization Recommendation",
journal = j-TWEB,
volume = "16",
number = "3",
pages = "11:1--11:??",
month = aug,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3538703",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Nov 16 08:39:27 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3538703",
abstract = "Visualization recommendation work has focused solely
on scoring visualizations based on the underlying
dataset, and not the actual user and their past
visualization feedback. These systems recommend the
same visualizations for every user, despite that the
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Raponi:2022:FNP,
author = "Simone Raponi and Zeinab Khalifa and Gabriele Oligeri
and Roberto {Di Pietro}",
title = "Fake News Propagation: a Review of Epidemic Models,
Datasets, and Insights",
journal = j-TWEB,
volume = "16",
number = "3",
pages = "12:1--12:??",
month = aug,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3522756",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Nov 16 08:39:27 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3522756",
abstract = "Fake news propagation is a complex phenomenon
influenced by a multitude of factors whose
identification and impact assessment is challenging.
Although many models have been proposed in the
literature, the one capturing all the properties of a
real fake-. \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Squicciarini:2022:EUG,
author = "Anna Squicciarini and Sarah Rajtmajer and Yang Gao and
Justin Semonsen and Andrew Belmonte and Pratik
Agarwal",
title = "An Extended Ultimatum Game for Multi-Party Access
Control in Social Networks",
journal = j-TWEB,
volume = "16",
number = "3",
pages = "13:1--13:??",
month = aug,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3555351",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Nov 16 08:39:27 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3555351",
abstract = "In this article, we aim to answer an important set of
questions about the potential longitudinal effects of
repeated sharing and privacy settings decisions over
jointly managed content among users in a social
network. We model user interactions through a
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Oswald:2022:SIA,
author = "C. Oswald and Sona Elza Simon and Arnab Bhattacharya",
title = "{SpotSpam}: Intention Analysis-driven {SMS} Spam
Detection Using {BERT} Embeddings",
journal = j-TWEB,
volume = "16",
number = "3",
pages = "14:1--14:??",
month = aug,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3538491",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Nov 16 08:39:27 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3538491",
abstract = "Short Message Service (SMS) is one of the widely used
mobile applications for global communication for
personal and business purposes. Its widespread use for
customer interaction, business updates, and reminders
has made it a billion-dollar industry in \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Jha:2022:IPP,
author = "Nikhil Jha and Martino Trevisan and Luca Vassio and
Marco Mellia",
title = "The {Internet} with Privacy Policies: Measuring The
{Web} Upon Consent",
journal = j-TWEB,
volume = "16",
number = "3",
pages = "15:1--15:??",
month = aug,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3555352",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Wed Nov 16 08:39:27 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3555352",
abstract = "To protect user privacy, legislators have regulated
the use of tracking technologies, mandating the
acquisition of users' consent before collecting data.
As a result, websites started showing more and more
consent management modules-i.e., Consent Banners-.
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Frosini:2022:OTF,
author = "Riccardo Frosini and Alexandra Poulovassilis and Peter
T. Wood and Andrea Cal{\'\i}",
title = "Optimisation Techniques for Flexible {SPARQL}
Queries",
journal = j-TWEB,
volume = "16",
number = "4",
pages = "16:1--16:??",
month = nov,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3532855",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Dec 9 06:51:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3532855",
abstract = "Resource Description Framework datasets can be queried
using the SPARQL language but are often irregularly
structured and incomplete, which may make precise query
formulation hard for users. The SPARQL$^{AR}$ language
extends SPARQL 1.1 with two operators-\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Chaqfeh:2022:JWD,
author = "Moumena Chaqfeh and Russell Coke and Jacinta Hu and
Waleed Hashmi and Lakshmi Subramanian and Talal Rahwan
and Yasir Zaki",
title = "\pkg{JSAnalyzer}: a {Web} Developer Tool for
Simplifying Mobile {Web} Pages through Non-critical
{JavaScript} Elimination",
journal = j-TWEB,
volume = "16",
number = "4",
pages = "17:1--17:??",
month = nov,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3550358",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Dec 9 06:51:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/java2020.bib;
http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3550358",
abstract = "The amount of JavaScript used in web pages has
substantially grown in the past decade, leading to
large and complex pages that are computationally
intensive for handheld mobile devices. Due to the
increasing usage of these devices to access today's
web, \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Upadhyaya:2022:SFV,
author = "Apoorva Upadhyaya and Joydeep Chandra",
title = "Spotting Flares: The Vital Signs of the Viral Spread
of Tweets Made During Communal Incidents",
journal = j-TWEB,
volume = "16",
number = "4",
pages = "18:1--18:??",
month = nov,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3550357",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Dec 9 06:51:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3550357",
abstract = "With the increasing use of Twitter for encouraging
users to instigate violent behavior with hate and
racial content, it becomes necessary to investigate the
uniqueness in the dynamics of the spread of tweets made
during violent communal incidents and the \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Chen:2022:DAC,
author = "Qi Chen and Guohui Li and Quan Zhou and Si Shi and
Deqing Zou",
title = "Double Attention Convolutional Neural Network for
Sequential Recommendation",
journal = j-TWEB,
volume = "16",
number = "4",
pages = "19:1--19:??",
month = nov,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3555350",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Dec 9 06:51:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3555350",
abstract = "The explosive growth of e-commerce and online service
has led to the development of recommender system.
Aiming to provide a list of items to meet a user's
personalized need by analyzing his/her interaction $^1$
history, recommender system has been widely \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2022:BBS,
author = "Xi Wang and Iadh Ounis and Craig Macdonald",
title = "\pkg{BanditProp}: Bandit Selection of Review
Properties for Effective Recommendation",
journal = j-TWEB,
volume = "16",
number = "4",
pages = "20:1--20:??",
month = nov,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3532859",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Dec 9 06:51:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3532859",
abstract = "Many recent recommendation systems leverage the large
quantity of reviews placed by users on items. However,
it is both challenging and important to accurately
measure the usefulness of such reviews for effective
recommendation. In particular, users have \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Moon:2022:MME,
author = "Taegeun Moon and Hyoungshick Kim and Sangwon Hyun",
title = "\pkg{Mutexion}: Mutually Exclusive Compression System
for Mitigating Compression Side-Channel Attacks",
journal = j-TWEB,
volume = "16",
number = "4",
pages = "21:1--21:??",
month = nov,
year = "2022",
CODEN = "????",
DOI = "https://doi.org/10.1145/3532850",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Fri Dec 9 06:51:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3532850",
abstract = "To enhance the performance of web services, web
servers often compress data to be delivered.
Unfortunately, the data compression technique has also
introduced a side effect called compression
side-channel attacks (CSCA). CSCA allows eavesdroppers
to \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Haider:2023:CLV,
author = "Waqar Haider and Yeliz Yesilada",
title = "Classification of Layout vs. Relational Tables on the
{Web}: Machine Learning with Rendered Pages",
journal = j-TWEB,
volume = "17",
number = "1",
pages = "1:1--1:??",
month = feb,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3555349",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:44 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3555349",
abstract = "Table mining on the web is an open problem, and none
of the previously proposed techniques provides a
complete solution. Most research focuses on the
structure of the HTML document, but because of the
nature and structure of the web, it is still a
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Xiao:2023:DKE,
author = "Yunming Xiao and Matteo Varvello and Marc Warrior and
Aleksandar Kuzmanovic",
title = "Decoding the {Kodi} Ecosystem",
journal = j-TWEB,
volume = "17",
number = "1",
pages = "2:1--2:??",
month = feb,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3563700",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:44 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3563700",
abstract = "Free and open-source media centers are experiencing a
boom in popularity for the convenience they offer users
seeking to remotely consume digital content. Kodi is
today's most popular home media center, with millions
of users worldwide. Kodi's popularity derives from its
ability to centralize the sheer amount of media content
available on the Web, both free and copyrighted.
Researchers have been hinting at potential security
concerns around Kodi, due to add-ons injecting unwanted
content as well as user settings linked with security
holes. Motivated by these observations, this article
conducts the first comprehensive analysis of the Kodi
ecosystem: 15,000 Kodi users from 104 countries, 11,000
unique add-ons, and data collected over 9 months.
Our work makes three important contributions. Our first
contribution is that we build ``crawling'' software
(de-Kodi) which can automatically install a Kodi
add-on, explore its menu, and locate (video) content.
This is challenging for two main reasons. First, Kodi
largely relies on visual information and user input
which intrinsically complicates automation. Second, the
potential sheer size of this ecosystem (i.e., the
number of available add-ons) requires a highly scalable
crawling solution. Our second contribution is that we
develop a solution to discover Kodi add-ons. Our
solution combines Web crawling of popular websites
where Kodi add-ons are published (LazyKodi and GitHub)
and SafeKodi, a Kodi add-on we have developed which
leverages the help of Kodi users to learn which add-ons
are used in the wild and, in return, offers information
about how safe these add-ons are, e.g., do they track
user activity or contact sketchy URLs/IP addresses. Our
third contribution is a classifier to passively detect
Kodi traffic and add-on usage in the wild.
Our analysis of the Kodi ecosystem reveals the
following findings. We find that most installed add-ons
are unofficial but safe to use. Still, 78\% of the
users have installed at least one unsafe add-on, and
even worse, such add-ons are among the most popular. In
response to the information offered by SafeKodi,
one-third of the users reacted by disabling some of
their add-ons. However, the majority of users ignored
our warnings for several months attracted by the
content such unsafe add-ons have to offer. Last but not
least, we show that Kodi's auto-update, a feature
active for 97.6\% of SafeKodi users, makes Kodi users
easily identifiable by their ISPs. While passively
identifying which Kodi add-on is in use is, as
expected, much harder, we also find that many
unofficial add-ons do not use HTTPS yet, making their
passive detection straightforward.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2023:CPS,
author = "Xiao Wang and Craig MacDonald and Nicola Tonellotto
and Iadh Ounis",
title = "{ColBERT-PRF}: Semantic Pseudo-Relevance Feedback for
Dense Passage and Document Retrieval",
journal = j-TWEB,
volume = "17",
number = "1",
pages = "3:1--3:??",
month = feb,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3572405",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:44 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3572405",
abstract = "Pseudo-relevance feedback mechanisms, from Rocchio to
the relevance models, have shown the usefulness of
expanding and reweighting the users' initial queries
using information occurring in an initial set of
retrieved documents, known as the pseudo-. \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zou:2023:PTL,
author = "Lixin Zou and Weixue Lu and Yiding Liu and Hengyi Cai
and Xiaokai Chu and Dehong Ma and Daiting Shi and Yu
Sun and Zhicong Cheng and Simiu Gu and Shuaiqiang Wang
and Dawei Yin",
title = "Pre-trained Language Model-based Retrieval and Ranking
for {Web} Search",
journal = j-TWEB,
volume = "17",
number = "1",
pages = "4:1--4:??",
month = feb,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3568681",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:44 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3568681",
abstract = "Pre-trained language representation models (PLMs) such
as BERT and Enhanced Representation through kNowledge
IntEgration (ERNIE) have been integral to achieving
recent improvements on various downstream tasks,
including information retrieval. However, it \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Chen:2023:KED,
author = "Lei Chen and Jie Cao and Weichao Liang and Jia Wu and
Qiaolin Ye",
title = "Keywords-enhanced Deep Reinforcement Learning Model
for Travel Recommendation",
journal = j-TWEB,
volume = "17",
number = "1",
pages = "5:1--5:??",
month = feb,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3570959",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:44 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3570959",
abstract = "Tourism is an important industry and a popular
entertainment activity involving billions of visitors
per annum. One challenging problem tourists face is
identifying satisfactory products from vast tourism
information. Most of travel recommendation methods
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2023:ECR,
author = "Yingxu Wang and Xiaoru Chen and Jinyuan Fang and
Zaiqiao Meng and Shangsong Liang",
title = "Enhancing Conversational Recommendation Systems with
Representation Fusion",
journal = j-TWEB,
volume = "17",
number = "1",
pages = "6:1--6:??",
month = feb,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3577034",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:44 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3577034",
abstract = "Conversational Recommendation Systems (CRSs) aim to
improve recommendation performance by utilizing
information from a conversation session. A CRS first
constructs questions and then asks users for their
feedback in each conversation session to refine
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Chen:2023:FWO,
author = "Chung-Chi Chen and Hen-Hsen Huang and Hiroya Takamura
and Makoto P. Kato and Yu-Lieh Huang",
title = "{FinTech} on the {Web}: an Overview",
journal = j-TWEB,
volume = "17",
number = "2",
pages = "7:1--7:??",
month = may,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3572404",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:45 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3572404",
abstract = "In this article, we provide an overview of ACM TWEB's
special issue, Financial Technology on the Web. This
special issue covers diverse topics: (1) a new
architecture for leveraging online news to investment
and risk management, (2) a cross-platform \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Ang:2023:IRM,
author = "Gary Ang and Ee-Peng Lim",
title = "Investment and Risk Management with Online News and
Heterogeneous Networks",
journal = j-TWEB,
volume = "17",
number = "2",
pages = "8:1--8:??",
month = may,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3532858",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:45 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3532858",
abstract = "Stock price movements in financial markets are
influenced by large volumes of news from diverse
sources on the web, e.g., online news outlets, blogs,
social media. Extracting useful information from online
news for financial tasks, e.g., forecasting stock
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Bouadjenek:2023:UCA,
author = "Mohamed Reda Bouadjenek and Scott Sanner and Ga Wu",
title = "A User-Centric Analysis of Social Media for Stock
Market Prediction",
journal = j-TWEB,
volume = "17",
number = "2",
pages = "9:1--9:??",
month = may,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3532856",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:45 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3532856",
abstract = "Social media platforms such as Twitter or StockTwits
are widely used for sharing stock market opinions
between investors, traders, and entrepreneurs.
Empirically, previous work has shown that the content
posted on these social media platforms can be
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Kitzler:2023:DDF,
author = "Stefan Kitzler and Friedhelm Victor and Pietro Saggese
and Bernhard Haslhofer",
title = "Disentangling Decentralized Finance {(DeFi)}
Compositions",
journal = j-TWEB,
volume = "17",
number = "2",
pages = "10:1--10:??",
month = may,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3532857",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:45 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3532857",
abstract = "We present a measurement study on compositions of
Decentralized Finance (DeFi) protocols, which aim to
disrupt traditional finance and offer services on top
of distributed ledgers, such as Ethereum. Understanding
DeFi compositions is of great importance, \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Piccardi:2023:LSC,
author = "Tiziano Piccardi and Martin Gerlach and Akhil Arora
and Robert West",
title = "A Large-Scale Characterization of How Readers Browse
{Wikipedia}",
journal = j-TWEB,
volume = "17",
number = "2",
pages = "11:1--11:??",
month = may,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580318",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:45 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580318",
abstract = "Despite the importance and pervasiveness of Wikipedia
as one of the largest platforms for open knowledge,
surprisingly little is known about how people navigate
its content when seeking information. To bridge this
gap, we present the first systematic \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Sun:2023:ICW,
author = "Chang-Ai Sun and An Fu and Jingting Jia and Meng Li
and Jun Han",
title = "Improving Conformance of {Web} Services: a
Constraint-based Model-driven Approach",
journal = j-TWEB,
volume = "17",
number = "2",
pages = "12:1--12:??",
month = may,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580515",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:45 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580515",
abstract = "Web services have been widely used to develop complex
distributed software systems in the context of Service
Oriented Architecture (SOA). As a standard for
describing Web services, the Web Service Description
Language (WSDL) provides a universal mechanism
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Jain:2023:OLI,
author = "Lokesh Jain and Rahul Katarya and Shelly Sachdeva",
title = "Opinion Leaders for Information Diffusion Using Graph
Neural Network in Online Social Networks",
journal = j-TWEB,
volume = "17",
number = "2",
pages = "13:1--13:??",
month = may,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580516",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Mon Apr 17 18:10:45 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580516",
abstract = "Various opportunities are available to depict
different domains due to the diverse nature of social
networks and researchers' insatiable. An opinion leader
is a human entity or cluster of people who can redirect
human assessment strategy by intellectual \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Peng:2023:ISI,
author = "Hao Peng and Jian Yang and Jia Wu and Philip S. Yu",
title = "Introduction to the Special Issue on Advanced Graph
Mining on the {Web}: Theory, Algorithms, and
Applications: {Part 1}",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "14:1--14:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3579360",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3579360",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Yang:2023:RAS,
author = "Yingguang Yang and Renyu Yang and Yangyang Li and Kai
Cui and Zhiqin Yang and Yue Wang and Jie Xu and Haiyong
Xie",
title = "{RoSGAS}: Adaptive Social Bot Detection with
Reinforced Self-supervised {GNN} Architecture Search",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "15:1--15:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3572403",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3572403",
abstract = "Social bots are referred to as the automated accounts
on social networks that make attempts to behave like
humans. While Graph Neural Networks (GNNs) have been
massively applied to the field of social bot detection,
a huge amount of domain expertise and \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Du:2023:NRT,
author = "Haohua Du and Yue Wang and Xiaoya Xu and Mingsheng
Liu",
title = "{Niffler}: Real-time Device-level Anomalies Detection
in Smart Home",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "16:1--16:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3586073",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3586073",
abstract = "Device-level security has become a major concern in
smart home systems. Detecting problems in smart home
systems strives to increase accuracy in near real time
without hampering the regular tasks of the smart home.
The current state of the art in detecting \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Sun:2023:GDR,
author = "Li Sun and Yang Du and Shuai Gao and Junda Ye and
Feiyang Wang and Fuxin Ren and Mingchen Liang and Yue
Wang and Shuhai Wang",
title = "{GroupAligner}: a Deep Reinforcement Learning with
Domain Adaptation for Social Group Alignment",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "17:1--17:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580509",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580509",
abstract = "Social network alignment, which aims to uncover the
correspondence across different social networks, shows
fundamental importance in a wide spectrum of
applications such as cross-domain recommendation and
information propagation. In the literature, the
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhu:2023:MTG,
author = "Guixiang Zhu and Jie Cao and Lei Chen and Youquan Wang
and Zhan Bu and Shuxin Yang and Jianqing Wu and Zhiping
Wang",
title = "A Multi-Task Graph Neural Network with Variational
Graph Auto-Encoders for Session-Based Travel Packages
Recommendation",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "18:1--18:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3577032",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3577032",
abstract = "Session-based travel packages recommendation aims to
predict users' next click based on their current and
historical sessions recorded by Online Travel Agencies
(OTAs). Recently, an increasing number of studies
attempted to apply Graph Neural Networks \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Ahmed:2023:GAN,
author = "Usman Ahmed and Jerry Chun-Wei Lin and Gautam
Srivastava",
title = "Graph Attention Network for Text Classification and
Detection of Mental Disorder",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "19:1--19:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3572406",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3572406",
abstract = "A serious issue in today's society is Depression,
which can have a devastating impact on a person's
ability to cope in daily life. Numerous studies have
examined the use of data generated directly from users
using social media to diagnose and detect \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Li:2023:TIU,
author = "Qian Li and Jianxin Li and Lihong Wang and Cheng Ji
and Yiming Hei and Jiawei Sheng and Qingyun Sun and
Shan Xue and Pengtao Xie",
title = "Type Information Utilized Event Detection via
Multi-Channel {GNNs} in Electrical Power Systems",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "20:1--20:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3577031",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3577031",
abstract = "Event detection in power systems aims to identify
triggers and event types, which helps relevant
personnel respond to emergencies promptly and
facilitates the optimization of power supply
strategies. However, the limited length of short
electrical record \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2023:HGT,
author = "Shuhai Wang and Xin Liu and Xiao Pan and Hanjie Xu and
Mingrui Liu",
title = "Heterogeneous Graph Transformer for Meta-structure
Learning with Application in Text Classification",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "21:1--21:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580508",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580508",
abstract = "The prevalent heterogeneous Graph Neural Network (GNN)
models learn node and graph representations using
pre-defined meta-paths or only automatically
discovering meta-paths. However, the existing methods
suffer from information loss due to neglecting
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Gong:2023:RMC,
author = "Jibing Gong and Yao Wan and Ye Liu and Xuewen Li and
Yi Zhao and Cheng Wang and Yuting Lin and Xiaohan Fang
and Wenzheng Feng and Jingyi Zhang and Jie Tang",
title = "Reinforced {MOOCs} Concept Recommendation in
Heterogeneous Information Networks",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "22:1--22:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580510",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580510",
abstract = "Massive open online courses (MOOCs), which offer open
access and widespread interactive participation through
the internet, are quickly becoming the preferred method
for online and remote learning. Several MOOC platforms
offer the service of course \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "22",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Shang:2023:CST,
author = "Zhihua Shang and Hongtao Xie and Lingyun Yu and
Zhengjun Zha and Yongdong Zhang",
title = "Constructing Spatio-Temporal Graphs for Face Forgery
Detection",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "23:1--23:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580512",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580512",
abstract = "Recently, advanced development of facial manipulation
techniques threatens web information security, thus,
face forgery detection attracts a lot of attention. It
is clear that both spatial and temporal information of
facial videos contains the crucial \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "23",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Sheshbolouki:2023:SES,
author = "Aida Sheshbolouki and M. Tamer {\"O}zsu",
title = "{sGrow}: Explaining the Scale-Invariant Strength
Assortativity of Streaming Butterflies",
journal = j-TWEB,
volume = "17",
number = "3",
pages = "24:1--24:??",
month = aug,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3572408",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Sat Aug 19 07:32:23 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3572408",
abstract = "Bipartite graphs are rich data structures with
prevalent applications and characteristic structural
features. However, less is known about their growth
patterns, particularly in streaming settings. Current
works study the patterns of static or aggregated
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "24",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Milton:2023:UES,
author = "Ashlee Milton and Maria Soledad Pera",
title = "Into the Unknown: Exploration of Search Engines'
Responses to Users with Depression and Anxiety",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "25:1--25:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580283",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580283",
abstract = "Researchers worldwide have explored the behavioral
nuances that emerge from interactions of individuals
afflicted by mental health disorders (MHD) with
persuasive technologies, mainly social media. Yet,
there is a gap in the analysis pertaining to a
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "25",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Amagata:2023:RMI,
author = "Daichi Amagata and Takahiro Hara",
title = "Reverse Maximum Inner Product Search: Formulation,
Algorithms, and Analysis",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "26:1--26:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3587215",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3587215",
abstract = "The maximum inner product search (MIPS), which finds
the item with the highest inner product with a given
query user, is an essential problem in the
recommendation field. Usually e-commerce companies face
situations where they want to promote and sell new
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "26",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Pajola:2023:NRH,
author = "Luca Pajola and Dongkai Chen and Mauro Conti and V. S.
Subrahmanian",
title = "A Novel Review Helpfulness Measure Based on the
User-Review-Item Paradigm",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "27:1--27:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3585280",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3585280",
abstract = "Review platforms are viral online services where users
share and read opinions about products (e.g., a
smartphone) or experiences (e.g., a meal at a
restaurant). Other users may be influenced by such
opinions when deciding what to buy. The usability of
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "27",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Berlin:2023:REW,
author = "John Berlin and Mat Kelly and Michael L. Nelson and
Michele C. Weigle",
title = "To Re-experience the {Web}: a Framework for the
Transformation and Replay of Archived {Web} Pages",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "28:1--28:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3589206",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3589206",
abstract = "When replaying an archived web page, or memento, the
fundamental expectation is that the page should be
viewable and function exactly as it did at the archival
time. However, this expectation requires web archives
upon replay to modify the page and its \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "28",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Liu:2023:CCU,
author = "Zhenfang Liu and Jianxiong Ye and Zhaonian Zou",
title = "Closeness Centrality on Uncertain Graphs",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "29:1--29:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3604912",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3604912",
abstract = "Centrality is a family of metrics for characterizing
the importance of a vertex in a graph. Although a large
number of centrality metrics have been proposed, a
majority of them ignores uncertainty in graph data. In
this article, we formulate closeness \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "29",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Kilic:2023:PSO,
author = "Yasir Kilic and Ali Inan",
title = "Privacy Scoring over {OSNs}: Shared Data Granularity
as a Latent Dimension",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "30:1--30:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3604909",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3604909",
abstract = "Privacy scoring aims at measuring the privacy
violation risk of a user over an online social network
(OSN) based on attribute values shared in the user's
OSN profile page and the user's position in the
network. Existing studies on privacy scoring rely on
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "30",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Sun:2023:PTA,
author = "Ke Sun and Tieyun Qian and Chenliang Li and Xuan Ma
and Qing Li and Ming Zhong and Yuanyuan Zhu and Mengchi
Liu",
title = "Pre-Training Across Different Cities for Next {POI}
Recommendation",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "31:1--31:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3605554",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3605554",
abstract = "The Point-of-Interest (POI) transition behaviors could
hold absolute sparsity and relative sparsity very
differently for different cities. Hence, it is
intuitive to transfer knowledge across cities to
alleviate those data sparsity and imbalance problems
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "31",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Watanabe:2023:LCB,
author = "Willian Massami Watanabe and Danilo Alves dos Santos
and Claiton de Oliveira",
title = "Layout Cross-Browser Failure Classification for Mobile
Responsive Design {Web} Applications: Combining
Classification Models Using Feature Selection",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "32:1--32:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580518",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580518",
abstract = "Cross-browser incompatibilities (XBIs) are defined as
inconsistencies that can be observed in Web
applications when they are rendered in a specific
browser compared to others. These inconsistencies are
associated with differences in the way each browser
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "32",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wu:2023:DBC,
author = "Bin Wu and Zaiqiao Meng and Shangsong Liang",
title = "Dynamic {Bayesian} Contrastive Predictive Coding Model
for Personalized Product Search",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "33:1--33:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3609225",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3609225",
abstract = "In this article, we study the problem of dynamic
personalized product search. Due to the data-sparsity
problem in the real world, existing methods suffer from
the challenge of data inefficiency. We address the
challenge by proposing a Dynamic Bayesian \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "33",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhao:2023:DGM,
author = "Chenye Zhao and Cornelia Caragea",
title = "Deep Gated Multi-modal Fusion for Image Privacy
Prediction",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "34:1--34:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3608446",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3608446",
abstract = "With the rapid development of technologies in mobile
devices, people can post their daily lives on social
networking sites such as Facebook, Flickr, and
Instagram. This leads to new privacy concerns due to
people's lack of understanding that private \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "34",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Pathak:2023:UCR,
author = "Royal Pathak and Francesca Spezzano and Maria Soledad
Pera",
title = "Understanding the Contribution of Recommendation
Algorithms on Misinformation Recommendation and
Misinformation Dissemination on Social Networks",
journal = j-TWEB,
volume = "17",
number = "4",
pages = "35:1--35:??",
month = nov,
year = "2023",
CODEN = "????",
DOI = "https://doi.org/10.1145/3616088",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3616088",
abstract = "Social networks are a platform for individuals and
organizations to connect with each other and inform,
advertise, spread ideas, and ultimately influence
opinions. These platforms have been known to propel
misinformation. We argue that this could be \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "35",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Uzun:2024:SRI,
author = "Erdin{\c{c}} Uzun",
title = "Scraping Relevant Images from {Web} Pages without
Download",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "1:1--1:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3616849",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3616849",
abstract = "Automatically scraping relevant images from web pages
is an error-prone and time-consuming task, leading
experts to prefer manually preparing extraction
patterns for a website. Existing web scraping tools are
built on these patterns. However, this manual
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "1",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wu:2024:CCG,
author = "Huizi Wu and Cong Geng and Hui Fang",
title = "Causality and Correlation Graph Modeling for Effective
and Explainable Session-Based Recommendation",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "2:1--2:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3593313",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3593313",
abstract = "Session-based recommendation, which has witnessed a
booming interest recently, focuses on predicting a
user's next interested item(s) based on an anonymous
session. Most existing studies adopt complex deep
learning techniques (e.g., graph neural networks)
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "2",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Jones:2024:SWA,
author = "Shawn M. Jones and Martin Klein and Michele C. Weigle
and Michael L. Nelson",
title = "Summarizing {Web} Archive Corpora via Social Media
Storytelling by Automatically Selecting and Visualizing
Exemplars",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "3:1--3:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3606030",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3606030",
abstract = "People often create themed collections to make sense
of an ever-increasing number of archived web pages.
Some of these collections contain hundreds of thousands
of documents. Thousands of collections exist, many
covering the same topic. Few collections \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "3",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhang:2024:SSE,
author = "Lei Zhang and Wuji Zhang and Likang Wu and Ming He and
Hongke Zhao",
title = "{SHGCN}: Socially Enhanced Heterogeneous Graph
Convolutional Network for Multi-behavior Prediction",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "4:1--4:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3617510",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3617510",
abstract = "In recent years, multi-behavior information has been
utilized to address data sparsity and cold-start
issues. The general multi-behavior models capture
multiple behaviors of users to make the representation
of relevant features more fine-grained and \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "4",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Emmert-Streib:2024:HTB,
author = "Frank Emmert-Streib and Shailesh Tripathi and Matthias
Dehmer",
title = "Human Team Behavior and Predictability in the
Massively Multiplayer Online Game {WOT} Blitz",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "5:1--5:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3617509",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3617509",
abstract = "Massively multiplayer online games (MMOGs) played on
the Web provide a new form of social, computer-mediated
interactions that allow the connection of millions of
players worldwide. The rules governing team-based MMOGs
are typically complex and \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "5",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Shrestha:2024:JCE,
author = "Anu Shrestha and Jason Duran and Francesca Spezzano
and Edoardo Serra",
title = "Joint Credibility Estimation of News, User, and
Publisher via Role-relational Graph Convolutional
Networks",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "6:1--6:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3617418",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3617418",
abstract = "The presence of fake news on online social media is
overwhelming and is responsible for having impacted
several aspects of people's lives, from health to
politics, the economy, and response to natural
disasters. Although significant effort has been made
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "6",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Ahmad:2024:EAW,
author = "Zubair Ahmad and Samuele Casarin and Stefano
Calzavara",
title = "An Empirical Analysis of {Web} Storage and Its
Applications to {Web} Tracking",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "7:1--7:28",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3623382",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3623382",
abstract = "In this article, we present a large-scale empirical
analysis of the use of web storage in the wild. By
using dynamic taint tracking at the level of JavaScript
and by performing an automated classification of the
detected information flows, we shed light on the key
characteristics of web storage uses in the Tranco Top
10k. Our analysis shows that web storage is routinely
accessed by third parties, including known web
trackers, who are particularly eager to have both read
and write access to persistent web storage information.
We then deep dive in web tracking as a prominent case
study: our analysis shows that web storage is not yet
as popular as cookies for tracking purposes; however,
taint tracking is useful to detect potential new
trackers not included in standard filter lists.
Moreover, we observe that many websites do not comply
with the General Data Protection Regulation directives
when it comes to their use of web storage.",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "7",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Sharma:2024:URP,
author = "Trishie Sharma and Rachit Agarwal and Sandeep Kumar
Shukla",
title = "Understanding Rug Pulls: an In-depth Behavioral
Analysis of Fraudulent {NFT} Creators",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "8:1--8:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3623376",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3623376",
abstract = "The explosive growth of non-fungible tokens (NFTs) on
Web3 has created a new frontier for digital art and
collectibles and an emerging space for fraudulent
activities. This study provides an in-depth analysis of
NFT rug pulls, the fraudulent schemes that \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "8",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Li:2024:MLS,
author = "Qingqing Li and Huifang Ma and Zhixin Li and Liang
Chang",
title = "Multiresolution Local Spectral Attributed Community
Search",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "9:1--9:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3624580",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3624580",
abstract = "Community search has become especially important in
graph analysis task, which aims to identify latent
members of a particular community from a few given
nodes. Most of the existing efforts in community search
focus on exploring the community structure \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "9",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Agarwal:2024:GBC,
author = "Vibhor Agarwal and Anthony P. Young and Sagar Joglekar
and Nishanth Sastry",
title = "A Graph-Based Context-Aware Model to Understand Online
Conversations",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "10:1--10:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3624579",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3624579",
abstract = "Online forums that allow for participatory engagement
between users have been transformative for the public
discussion of many important issues. However, such
conversations can sometimes escalate into full-blown
exchanges of hate and misinformation. \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "10",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Gao:2024:TOC,
author = "Guangliang Gao and Weichao Liang and Ming Yuan and
Hanwei Qian and Qun Wang and Jie Cao",
title = "Triangle-oriented Community Detection Considering Node
Features and Network Topology",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "11:1--11:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3626190",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3626190",
abstract = "The joint use of node features and network topology to
detect communities is called community detection in
attributed networks. Most of the existing work along
this line has been carried out through objective
function optimization and has proposed \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "11",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Ma:2024:CCA,
author = "Yutao Ma and Zesheng Wang and Liwei Huang and Jian
Wang",
title = "{CLHHN}: Category-aware Lossless Heterogeneous
Hypergraph Neural Network for Session-based
Recommendation",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "12:1--12:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3626569",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3626569",
abstract = "In recent years, session-based recommendation (SBR),
which seeks to predict the target user's next click
based on anonymous interaction sequences, has drawn
increasing interest for its practicality. The key to
completing the SBR task is modeling user \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "12",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Lin:2024:ARI,
author = "Fuqi Lin and Xuan Lu and Wei Ai and Huoran Li and Yun
Ma and Yulian Yang and Hongfei Deng and Qingxiang Wang
and Qiaozhu Mei and Xuanzhe Liu",
title = "Adoption of Recurrent Innovations: a Large-Scale Case
Study on Mobile App Updates",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "13:1--13:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3626189",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3626189",
abstract = "Modern technology innovations feature a successive and
even recurrent procedure. Intervals between old and new
generations of technology are shrinking, and the
Internet and Web services have facilitated the fast
adoption of an innovation even before the \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "13",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Belhadi:2024:RTE,
author = "Asma Belhadi and Man Zhang and Andrea Arcuri",
title = "Random Testing and Evolutionary Testing for Fuzzing
{GraphQL APIs}",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "14:1--14:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3609427",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3609427",
abstract = "The Graph Query Language (GraphQL) is a powerful
language for application programming interface (API)
manipulation in web services. It has been recently
introduced as an alternative solution for addressing
the limitations of RESTful APIs. This article
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "14",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Chen:2024:BPX,
author = "Ninghan Chen and Xihui Chen and Zhiqiang Zhong and Jun
Pang",
title = "Bridging Performance of {X} (formerly known as
{Twitter}) Users: a Predictor of Subjective Well-Being
During the Pandemic",
journal = j-TWEB,
volume = "18",
number = "1",
pages = "15:1--15:??",
month = feb,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3635033",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:13 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3635033",
abstract = "The outbreak of the COVID-19 pandemic triggered the
perils of misinformation over social media. By
amplifying the spreading speed and popularity of
trustworthy information, influential social media users
have been helping overcome the negative impacts of
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "15",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Peng:2024:ISI,
author = "Hao Peng and Jian Yang and Jia Wu and Philip S. Yu",
title = "Introduction to the Special Issue on Advanced Graph
Mining on the {Web}: Theory, Algorithms, and
Applications: {Part 2}",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "16:1--16:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3631941",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3631941",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "16",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2024:CGS,
author = "Luzhi Wang and Yizhen Zheng and Di Jin and Fuyi Li and
Yongliang Qiao and Shirui Pan",
title = "Contrastive Graph Similarity Networks",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "17:1--17:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580511",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580511",
abstract = "Graph similarity learning is a significant and
fundamental issue in the theory and analysis of graphs,
which has been applied in a variety of fields,
including object tracking, recommender systems,
similarity search, and so on. Recent methods for graph
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "17",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Qiao:2024:DCS,
author = "Ziyue Qiao and Pengyang Wang and Pengfei Wang and
Zhiyuan Ning and Yanjie Fu and Yi Du and Yuanchun Zhou
and Jianqiang Huang and Xian-Sheng Hua and Hui Xiong",
title = "A Dual-channel Semi-supervised Learning Framework on
Graphs via Knowledge Transfer and Meta-learning",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "18:1--18:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3577033",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3577033",
abstract = "This article studies the problem of semi-supervised
learning on graphs, which aims to incorporate
ubiquitous unlabeled knowledge (e.g., graph topology,
node attributes) with few-available labeled knowledge
(e.g., node class) to alleviate the scarcity \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "18",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zheng:2024:HIC,
author = "Xiaolin Zheng and Rui Wu and Zhongxuan Han and
Chaochao Chen and Linxun Chen and Bing Han",
title = "Heterogeneous Information Crossing on Graphs for
Session-Based Recommender Systems",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "19:1--19:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3572407",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3572407",
abstract = "Recommender systems are fundamental information
filtering techniques to recommend content or items that
meet users' personalities and potential needs. As a
crucial solution to address the difficulty of user
identification and unavailability of historical
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "19",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Luo:2024:SIM,
author = "Pengfei Luo and Xi Zhu and Tong Xu and Yi Zheng and
Enhong Chen",
title = "Semantic Interaction Matching Network for Few-Shot
Knowledge Graph Completion",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "20:1--20:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3589557",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3589557",
abstract = "The prosperity of knowledge graphs, as well as related
downstream applications, has raised the urgent need for
knowledge graph completion techniques that fully
support knowledge graph reasoning tasks, especially
under the circumstance of training data \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "20",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Yu:2024:LNU,
author = "Mei Yu and Kun Zhu and Mankun Zhao and Jian Yu and
Tianyi Xu and Di Jin and Xuewei Li and Ruiguo Yu",
title = "Learning Neighbor User Intention on User-Item
Interaction Graphs for Better Sequential
Recommendation",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "21:1--21:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580520",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580520",
abstract = "The task of sequential recommendation aims to predict
a user's preference by analyzing the user's historical
behaviours. Existing methods model item transitions
through leveraging sequential patterns. However, they
mainly consider the target user's \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "21",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2024:DAG,
author = "Pengfei Wang and Daqing Wu and Chong Chen and Kunpeng
Liu and Yanjie Fu and Jianqiang Huang and Yuanchun Zhou
and Jianfeng Zhan and Xiansheng Hua",
title = "Deep Adaptive Graph Clustering via {von Mises--Fisher}
Distributions",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "22:1--22:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580521",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580521",
abstract = "Graph clustering has been a hot research topic and is
widely used in many fields, such as community detection
in social networks. Lots of works combining
auto-encoder and graph neural networks have been
applied to clustering tasks by utilizing node
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "22",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhu:2024:ITG,
author = "Haorui Zhu and Fei Xiong and Hongshu Chen and Xi Xiong
and Liang Wang",
title = "Incorporating a Triple Graph Neural Network with
Multiple Implicit Feedback for Social Recommendation",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "23:1--23:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580517",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580517",
abstract = "Graph neural networks have been clearly proven to be
powerful in recommendation tasks since they can capture
high-order user-item interactions and integrate them
with rich attributes. However, they are still limited
by the cold-start problem and data \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "23",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Kumar:2024:CEL,
author = "Mukesh Kumar and Shivansh Mishra and Shashank Sheshar
Singh and Bhaskar Biswas",
title = "Community-enhanced Link Prediction in Dynamic
Networks",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "24:1--24:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580513",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580513",
abstract = "The growing popularity of online social networks is
quite evident nowadays and provides an opportunity to
allow researchers in finding solutions for various
practical applications. Link prediction is the
technique of understanding network structure and
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "24",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Liu:2024:BFG,
author = "Mingyi Liu and Zhiying Tu and Tonghua Su and Xianzhi
Wang and Xiaofei Xu and Zhongjie Wang",
title = "{BehaviorNet}: a Fine-grained Behavior-aware Network
for Dynamic Link Prediction",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "25:1--25:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3580514",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3580514",
abstract = "Dynamic link prediction has become a trending research
subject because of its wide applications in the web,
sociology, transportation, and bioinformatics.
Currently, the prevailing approach for dynamic link
prediction is based on graph neural networks, in
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "25",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Xiao:2024:PPI,
author = "Chunjing Xiao and Wanlin Ji and Yuxiang Zhang and
Shenkai Lv",
title = "{PIDKG}: Propagating Interaction Influence on the
Dynamic Knowledge Graph for Recommendation",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "26:1--26:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3593314",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3593314",
abstract = "Modeling the dynamic interactions between users and
items on knowledge graphs is crucial for improving the
accuracy of recommendation. Although existing methods
have made great progress in modeling the dynamic
knowledge graphs for recommendation, they \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "26",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Rieger:2024:NMC,
author = "Alisa Rieger and Tim Draws and Mari{\"e}t Theune and
Nava Tintarev",
title = "Nudges to Mitigate Confirmation Bias during {Web}
Search on Debated Topics: Support vs. Manipulation",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "27:1--27:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3635034",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3635034",
abstract = "When people use web search engines to find information
on debated topics, the search results they encounter
can influence opinion formation and practical
decision-making with potentially far-reaching
consequences for the individual and society. However,
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "27",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Yu:2024:BNB,
author = "Fangyu Yu and Peng Zhang and Xianghua Ding and Tun Lu
and Ning Gu",
title = "{BNoteHelper}: a Note-based Outline Generation Tool
for Structured Learning on Video-sharing Platforms",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "28:1--28:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3638775",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3638775",
abstract = "Usually generated by ordinary users and often not
particularly designed for learning, the videos on
video-sharing platforms are mostly not structured
enough to support learning purposes, although they are
increasingly leveraged for that. Most existing
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "28",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhang:2024:DAF,
author = "Peng Zhang and Qi Zhou and Tun Lu and Hansu Gu and
Ning Gu",
title = "{DeLink}: an Adversarial Framework for Defending
against Cross-site User Identity Linkage",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "29:1--29:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3643828",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3643828",
abstract = "Cross-site user identity linkage (UIL) aims to link
the identities of the same person across different
social media platforms. Social media practitioners and
service providers can construct composite user
portraits based on cross-site UIL, which helps
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "29",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Li:2024:HCP,
author = "Lingyao Li and Lizhou Fan and Shubham Atreja and Libby
Hemphill",
title = "{``HOT'' ChatGPT}: The Promise of {ChatGPT} in
Detecting and Discriminating Hateful, Offensive, and
Toxic Comments on Social Media",
journal = j-TWEB,
volume = "18",
number = "2",
pages = "30:1--30:??",
month = may,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3643829",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:14 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3643829",
abstract = "Harmful textual content is pervasive on social media,
poisoning online communities and negatively impacting
participation. A common approach to this issue is
developing detection models that rely on human
annotations. However, the tasks required to build
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "30",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Umair:2024:EFA,
author = "Muhammad Umair and Athman Bouguettaya and Abdallah
Lakhdari and Mourad Ouzzani and Yuyun Liu",
title = "{Exif2Vec}: a Framework to Ascertain Untrustworthy
Crowdsourced Images Using Metadata",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "31:1--31:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3645094",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3645094",
abstract = "In the context of social media, the integrity of
images is often dubious. To tackle this challenge, we
introduce Exif2Vec, a novel framework specifically
designed to discover modifications in social media
images. The proposed framework leverages an image'.
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "31",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zareie:2024:FIM,
author = "Ahmad Zareie and Rizos Sakellariou",
title = "Fuzzy Influence Maximization in Social Networks",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "32:1--32:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3650179",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3650179",
abstract = "Influence maximization is a fundamental problem in
social network analysis. This problem refers to the
identification of a set of influential users as initial
spreaders to maximize the spread of a message in a
network. When such a message is spread, some \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "32",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Shah:2024:EIA,
author = "Chirag Shah and Emily M. Bender",
title = "Envisioning Information Access Systems: What Makes for
Good Tools and a Healthy {Web}?",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "33:1--33:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3649468",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3649468",
abstract = "We observe a recent trend toward applying large
language models (LLMs) in search and positioning them
as effective information access systems. While the
interfaces may look appealing and the apparent breadth
of applicability is exciting, we are concerned
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "33",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zhang:2024:HGN,
author = "Guangping Zhang and Dongsheng Li and Hansu Gu and Tun
Lu and Ning Gu",
title = "Heterogeneous Graph Neural Network with Personalized
and Adaptive Diversity for News Recommendation",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "34:1--34:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3649886",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3649886",
abstract = "The emergence of online media has facilitated the
dissemination of news, but has also introduced the
problem of information overload. To address this issue,
providing users with accurate and diverse news
recommendations has become increasingly important.
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "34",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Poddar:2024:MQC,
author = "Soham Poddar and Rajdeep Mukherjee and Azlaan Samad
and Niloy Ganguly and Saptarshi Ghosh",
title = "{MuLX-QA}: Classifying Multi-Labels and Extracting
Rationale Spans in Social Media Posts",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "35:1--35:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3653303",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3653303",
abstract = "While social media platforms play an important role in
our daily lives in obtaining the latest news and trends
from across the globe, they are known to be prone to
widespread proliferation of harmful information in
different forms leading to \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "35",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Maceiras:2024:KTC,
author = "Ma{\"e}l Maceiras and Kavous Salehzadeh Niksirat and
Ga{\"e}l Bernard and Benoit Garbinato and Mauro
Cherubini and Mathias Humbert and K{\'e}vin Huguenin",
title = "Know their Customers: an Empirical Study of Online
Account Enumeration Attacks",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "37:1--37:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3664201",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3664201",
abstract = "Internet users possess accounts on dozens of online
services where they are often identified by one of
their e-mail addresses. They often use the same address
on multiple services and for communicating with their
contacts. In this paper, we investigate \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "37",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Ang:2024:LDM,
author = "Gary Ang and Ee-Peng Lim",
title = "Learning Dynamic Multimodal Network Slot Concepts from
the {Web} for Forecasting Environmental, Social and
Governance Ratings",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "38:1--38:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3663674",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3663674",
abstract = "Dynamic multimodal networks are networks with node
attributes from different modalities where the
attributes and network relationships evolve across
time, i.e., both networks and multimodal attributes are
dynamic; for example, dynamic relationship \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "38",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Jha:2024:RIA,
author = "Nikhil Jha and Martino Trevisan and Emilio Leonardi
and Marco Mellia",
title = "Re-Identification Attacks against the Topics {API}",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "39:1--39:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3675400",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3675400",
abstract = "Recently, Google proposed the Topics API framework as
a privacy-friendly alternative for behavioural
advertising as a possible solution to balance user's
privacy and advertisement effectiveness. Using the
Topics API, the browser builds a user profile
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "39",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Skenderi:2024:IFD,
author = "Erjon Skenderi and Jukka Huhtam{\"a}ki and
Salla-Maaria Laaksonen and Kostas Stefanidis",
title = "{INCEPT}: a Framework for Duplicate Posts
Classification with Combined Text Representations",
journal = j-TWEB,
volume = "18",
number = "3",
pages = "40:1--40:??",
month = aug,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3677322",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Tue Aug 20 07:34:16 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3677322",
abstract = "Dealing with many of the problems related to the
quality of textual content online involves identifying
similar content. Algorithmic solutions for duplicate
content classification typically rely on text vector
representation, which maps textual \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "40",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Lei:2024:SIC,
author = "Wenqiang Lei and Richang Hong and Hamed Zamani and
Pawel Budzianowski and Vanessa Murdock and Emine
Yilmaz",
title = "Special Issue on Conversational Information Seeking",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "41:1--41:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3688392",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3688392",
abstract = "In this article, we provide an overview of ACM TWEB's
Special Issue on Conversational Information Seeking. It
highlights both research and practical applications in
this field. The article also discusses the future
potential of conversational information \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "41",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Frieder:2024:CHE,
author = "Ophir Frieder and Ida Mele and Cristina Ioana Muntean
and Franco Maria Nardini and Raffaele Perego and Nicola
Tonellotto",
title = "Caching Historical Embeddings in Conversational
Search",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "42:1--42:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3578519",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3578519",
abstract = "Rapid response, namely, low latency, is fundamental in
search applications; it is particularly so in
interactive search sessions, such as those encountered
in conversational settings. An observation with a
potential to reduce latency asserts that \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "42",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Rana:2024:UER,
author = "Arpit Rana and Scott Sanner and Mohamed Reda
Bouadjenek and Ronald {Di Carlantonio} and Gary
Farmaner",
title = "User Experience and the Role of Personalization in
Critiquing-Based Conversational Recommendation",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "43:1--43:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3597499",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3597499",
abstract = "Critiquing-where users propose directional preferences
to attribute values-has historically been a highly
popular method for conversational recommendation.
However, with the growing size of catalogs and item
attributes, it becomes increasingly difficult
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "43",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{An-An:2024:MSR,
author = "L. An-An and Lu Zimu and Xu Ning and Liu Min and Yan
Chenggang and Zheng Bolun and Lv Bo and Duan Yulong and
Shao Zhuang and Li Xuanya",
title = "Multi-stage reasoning on introspecting and revising
bias for visual question answering",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "44:1--44:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3616399",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3616399",
abstract = "Visual Question Answering (VQA) is a task that
involves predicting an answer to a question depending
on the content of an image. However, recent VQA methods
have relied more on language priors between the
question and answer rather than the image content.
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "44",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Li:2024:OHT,
author = "Miaoran Li and Baolin Peng and Jianfeng Gao and Zhu
Zhang",
title = "{OPERA}: Harmonizing Task-Oriented Dialogs and
Information Seeking Experience",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "45:1--45:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3623381",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3623381",
abstract = "Existing studies in conversational AI mostly treat
task-oriented dialog (TOD) and question answering (QA)
as separate tasks. Towards the goal of constructing a
conversational agent that can complete user tasks and
support information seeking, it is \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "45",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Shi:2024:ECP,
author = "Hongjian Shi and Meng Zhang and Ruhui Ma and Liwei Lin
and Rui Zhang and Haibing Guan",
title = "Edge Caching Placement Strategy based on Evolutionary
Game for Conversational Information Seeking in Edge
Cloud Computing",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "46:1--46:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3624985",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3624985",
abstract = "In Internet applications, network conversation is the
primary communication between the user and server. The
server needs to efficiently and quickly return the
corresponding service according to the conversation
sent by the user to improve the users' \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "46",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Meena:2024:DDC,
author = "Sunil Kumar Meena and Shashank Sheshar Singh and
Kuldeep Singh",
title = "{DCDIMB}: Dynamic Community-based Diversified
Influence Maximization using Bridge Nodes",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "47:1--47:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3664618",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3664618",
abstract = "Influence maximization (IM) is the fundamental study
of social network analysis. The IM problem finds the
top k nodes that have maximum influence in the network.
Most of the studies in IM focus on maximizing the
number of activated nodes in the static \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "47",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Wang:2024:XRA,
author = "Kai Wang and Michael Tong and Jun Pang and Jitao Wang
and Weili Han",
title = "{XRAD}: Ransomware Address Detection Method based on
Bitcoin Transaction Relationships",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "48:1--48:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3687487",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3687487",
abstract = "Recently, there is a surge in ransomware activities
that encrypt users' sensitive data and demand bitcoins
for ransom payments to conceal the criminal's identity.
It is crucial for regulatory agencies to identify as
many ransomware addresses as possible \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "48",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Meena:2024:CSO,
author = "Sunil Kumar Meena and Shashank Sheshar Singh and
Kuldeep Singh",
title = "Cuckoo Search Optimization-Based Influence
Maximization in Dynamic Social Networks",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "49:1--49:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3690644",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3690644",
abstract = "Online social networks are crucial in propagating
information and exerting influence through
word-of-mouth transmission. Influence maximization (IM)
is the fundamental task in social network analysis to
find the group of nodes that maximizes the influence
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "49",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Zeng:2024:EGN,
author = "Ruihong Zeng and Jinyuan Fang and Siwei Liu and
Zaiqiao Meng and Shangsong Liang",
title = "Enhancing Graph Neural Networks via Memorized Global
Information",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "50:1--50:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3689430",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3689430",
abstract = "Graph neural networks (GNNs) have gained significant
attention for their impressive results on different
graph-based tasks. The essential mechanism of GNNs is
the message-passing framework, whereby node
representations are aggregated from local \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "50",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
@Article{Qiu:2024:MTD,
author = "Jingyi Qiu and Aibo Song and Jiahui Jin and Jiaoyan
Chen and Xinyu Zhang and Xiaolin Fang and Tianbo
Zhang",
title = "Matching Tabular Data to Knowledge Graph with
Effective Core Column Set Discovery.",
journal = j-TWEB,
volume = "18",
number = "4",
pages = "51:1--51:??",
month = nov,
year = "2024",
CODEN = "????",
DOI = "https://doi.org/10.1145/3694979",
ISSN = "1559-1131 (print), 1559-114X (electronic)",
ISSN-L = "1559-1131",
bibdate = "Thu Oct 24 08:21:05 MDT 2024",
bibsource = "https://www.math.utah.edu/pub/tex/bib/tweb.bib",
URL = "https://dl.acm.org/doi/10.1145/3694979",
abstract = "Matching tabular data to a knowledge graph (KG) is
critical for understanding the semantic column types,
column relationships, and entities of a table. Existing
matching approaches rely heavily on core columns that
represent primary subject entities on \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "ACM Trans. Web",
articleno = "51",
fjournal = "ACM Transactions on the Web (TWEB)",
journal-URL = "https://dl.acm.org/loi/tweb",
}
