Paper Digest: WWW 2013 Highlights

May 12, 2013June 27, 2020 admin

The Web Conference (WWW) is one of the top internet conferences in the world.

To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper. Readers are encouraged to read these machine generated highlights / summaries to quickly get the main idea of each paper.

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Paper Digest Team
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TABLE 1: WWW 2013 Papers

	Title	Authors	Highlight
1	Real-time recommendation of diverse related articles	Sofiane Abbar, Sihem Amer-Yahia, Piotr Indyk, Sepideh Mahabadi	We formalize a novel recommendation problem where the goal is to find the closest most diverse articles to the one the user is currently browsing.
2	Multi-label learning with millions of labels: recommending advertiser bid phrases for web pages	Rahul Agrawal, Archit Gupta, Yashoteja Prabhu, Manik Varma	In this paper, we eschew this paradigm, and demonstrate that it is possible to efficiently predict the relevant subset of queries from a large set of monetizable ones by posing the problem as a multi-label learning task with each query being represented by a separate label.
3	Hierarchical geographical modeling of user locations from social media posts	Amr Ahmed, Liangjie Hong, Alexander J. Smola	This paper presents an integrated generative model of location and message content.
4	Distributed large-scale natural graph factorization	Amr Ahmed, Nino Shervashidze, Shravan Narayanamurthy, Vanja Josifovski, Alexander J. Smola	We propose a framework for large-scale graph decomposition and inference.
5	A CRM system for social media: challenges and experiences	Jitendra Ajmera, Hyung-iL Ahn, Meena Nagarajan, Ashish Verma, Danish Contractor, Stephen Dill, Matthew Denesuk	In this work we present our experiences in building a system that mines conversations on social platforms to identify and prioritize those posts and messages that are relevant to enterprises.
6	Here’s my cert, so trust me, maybe?: understanding TLS errors on the web	Devdatta Akhawe, Bernhard Amann, Matthias Vallentin, Robin Sommer	To guide that process, we perform a large-scale measurement study of common TLS warnings.
7	Towards a robust modeling of temporal interest change patterns for behavioral targeting	Mohamed Aly, Sandeep Pandey, Vanja Josifovski, Kunal Punera	In this paper we explore how the change in user behavior can be used to predict future actions and show how it complements the traditional models of decaying interest and action recency to build a complete picture about the user interests and better predict conversions.
8	The anatomy of LDNS clusters: findings and implications for web content delivery	Hussein A. Alzoubi, Michael Rabinovich, Oliver Spatscheck	We present a large-scale measurement of clusters of hosts sharing the same local DNS servers.
9	Steering user behavior with badges	Ashton Anderson, Daniel Huttenlocher, Jon Kleinberg, Jure Leskovec	In this paper, we study how badges can influence and steer user behavior on a site—leading both to increased participation and to changes in the mix of activities a user pursues on the site.
10	Cascading tree sheets and recombinant HTML: better encapsulation and retargeting of web content	Edward O. Benson, David R. Karger	This paper presents Cascading Tree Sheets (CTS), a CSS-like language for separating this presentational HTML from real content.
11	CopyCatch: stopping group attacks by spotting lockstep behavior in social networks	Alex Beutel, Wanhong Xu, Venkatesan Guruswami, Christopher Palow, Christos Faloutsos	In this paper we focus on the social network Facebook and the problem of discerning ill-gotten Page Likes, made by spammers hoping to turn a profit, from legitimate Page Likes.
12	Inferring the demographics of search users: social data meets search queries	Bin Bi, Milad Shokouhi, Michal Kosinski, Thore Graepel	In this paper, we offer a solution to this problem by showing how user demographic traits such as age and gender, and even political and religious views can be efficiently and accurately inferred based on their search query histories.
13	Strategyproof mechanisms for competitive influence in networks	Allan Borodin, Mark Braverman, Brendan Lucier, Joel Oren	We study this model from the perspective of a central mechanism, such as a social networking platform, that can optimize seed placement as a service for the advertisers.
14	Reactive crowdsourcing	Alessandro Bozzon, Marco Brambilla, Stefano Ceri, Andrea Mauri	Most crowdsourcing systems only provide limited and predefined controls; in contrast, we present an approach to crowdsourcing which provides fine-level, powerful and flexible controls.
15	On participation in group chats on Twitter	Ceren Budak, Rakesh Agrawal	To predict whether a user that attended her first session in a particular Twitter chat group will return to the group, we build 5F Model that captures five different factors: individual initiative, group characteristics, perceived receptivity, linguistic affinity and geographical proximity.
16	The role of web hosting providers in detecting compromised websites	Davide Canali, Davide Balzarotti, Aurélien Francillon	In this paper we test the ability of web hosting providers to detect compromised websites and react to user complaints.
17	Your browsing behavior for a big mac: economics of personal information online	Juan Pablo Carrascal, Christopher Riederer, Vijay Erramilli, Mauro Cherubini, Rodrigo de Oliveira	In this work, we rely on refined Experience Sampling – a data collection method that probes users to valuate their PII at the time and place where it was generated in order to minimize retrospective recall and hence increase measurement validity.
18	Is this app safe for children?: a comparison study of maturity ratings on Android and iOS applications	Ying Chen, Heng Xu, Yilu Zhou, Sencun Zhu	To address these issues, this research aims to systematically uncover the extent and severity of unreliable maturity ratings for mobile apps.
19	Traveling the silk road: a measurement analysis of a large anonymous online marketplace	Nicolas Christin	We perform a comprehensive measurement analysis of Silk Road, an anonymous, international online marketplace that operates as a Tor hidden service and uses Bitcoin as its exchange currency.
20	Group chats on Twitter	James Cook, Krishnaram Kenthapadi, Nina Mishra	We develop a definition of a group that is inspired by how sociologists define groups and present an algorithm for discovering groups.
21	How to grow more pairs: suggesting review targets for comparison-friendly review ecosystems	James Cook, Alex Fabrikant, Avinatan Hassidim	We consider the algorithmic challenges behind a novel interface that simplifies consumer research of online reviews by surfacing relevant comparable review bundles: reviews for two or more of the items being researched, all generated in similar enough circumstances to provide for easy comparison.
22	A framework for benchmarking entity-annotation systems	Marco Cornolti, Paolo Ferragina, Massimiliano Ciaramita	In this paper we design and implement a benchmarking framework for fair and exhaustive comparison of entity-annotation systems.
23	A framework for learning web wrappers from the crowd	Valter Crescenzi, Paolo Merialdo, Disheng Qiu	We introduce a framework to support a supervised wrapper inference system with training data generated by the crowd.
24	Lightweight server support for browser-based CSRF protection	Alexei Czeskis, Alexander Moshchuk, Tadayoshi Kohno, Helen J. Wang	In this paper, we present a browser/server solution, Allowed Referrer Lists (ARLs), that addresses the root cause of CSRFs and removes ambient authority for participating web sites that want to be resilient to CSRF attacks.
25	Aggregating crowdsourced binary ratings	Nilesh Dalvi, Anirban Dasgupta, Ravi Kumar, Vibhor Rastogi	In this paper we analyze a crowdsourcing system consisting of a set of users and a set of binary choice questions.
26	Optimal hashing schemes for entity matching	Nilesh Dalvi, Vibhor Rastogi, Anirban Dasgupta, Anish Das Sarma, Tamas Sarlos	In this paper, we consider the problem of devising blocking schemes for entity matching.
27	No country for old members: user lifecycle and linguistic change in online communities	Cristian Danescu-Niculescu-Mizil, Robert West, Dan Jurafsky, Jure Leskovec, Christopher Potts	We propose a framework for tracking linguistic change as it happens and for understanding how specific users react to these evolving norms.
28	Crowdsourced judgement elicitation with endogenous proficiency	Anirban Dasgupta, Arpita Ghosh	Our main contribution is a simple, new, mechanism for binary information elicitation for multiple tasks when agents have endogenous proficiencies, with the following properties: (i) Exerting maximum effort followed by truthful reporting of observations is a Nash equilibrium.
29	Timespent based models for predicting user retention	Kushal S. Dave, Vishal Vaingankar, Sumanth Kolar, Vasudeva Varma	In this paper, we attempt to address the problem of predicting user retention based on the user’s previous sessions.
30	Attributing authorship of revisioned content	Luca de Alfaro, Michael Shavlovsky	Since content can be deleted, only to be later re-inserted, we introduce a notion of authorship that requires comparing each new revision with the entire set of past revisions.
31	ClausIE: clause-based open information extraction	Luciano Del Corro, Rainer Gemulla	We propose ClausIE, a novel, clause-based approach to open information extraction, which extracts relations and their arguments from natural language text.
32	Pick-a-crowd: tell me what you like, and i’ll tell you what to do	Djellel Eddine Difallah, Gianluca Demartini, Philippe Cudré-Mauroux	In this paper, we propose and extensively evaluate a different Crowdsourcing approach based on a push methodology.
33	Compact explanation of data fusion decisions	Xin Luna Dong, Divesh Srivastava	We propose techniques that can efficiently generate correct and compact explanations.
34	From query to question in one click: suggesting synthetic questions to searchers	Gideon Dror, Yoelle Maarek, Avihai Mejer, Idan Szpektor	To this end, we introduce a learning-based approach that improves not only the relevance of the suggested questions to the original query, but also their grammatical correctness.
35	Perception and understanding of social annotations in web search	Jennifer Fernquist, Ed H. Chi	In this paper, we describe a study conducted with a new eyetracking mix-method using a live traffic search engine with the suggested design changes on real users using the same experimental procedures.
36	AMIE: association rule mining under incomplete evidence in ontological knowledge bases	Luis Antonio Galárraga, Christina Teflioudi, Katja Hose, Fabian Suchanek	In this paper, we develop a rule mining model that is explicitly tailored to support the OWA scenario.
37	PrefixSolve: efficiently solving multi-source multi-destination path queries on RDF graphs by sharing suffix computations	Sidan Gao, Kemafor Anyanwu	In this paper, we propose an optimization technique for general MSMD path queries that generalizes an efficient algebraic approach for solving a variety of single-source path problems.
38	When tolerance causes weakness: the case of injection-friendly browsers	Yossi Gilad, Amir Herzberg	We present a practical off-path TCP-injection attack for connections between current, non-buggy browsers and web-servers.
39	Exploiting innocuous activity for correlating users across sites	Oana Goga, Howard Lei, Sree Hari Krishnan Parthasarathi, Gerald Friedland, Robin Sommer, Renata Teixeira	We study how potential attackers can identify accounts on different social network sites that all belong to the same user, exploiting only innocuous activity that inherently comes with posted content.
40	The cost of annoying ads	Daniel G. Goldstein, R. Preston McAfee, Siddharth Suri	We conclude by proposing a theoretical model which relates ad quality to publisher market share, illustrating how our empirical findings could affect the economics of Internet advertising.
41	Researcher homepage classification using unlabeled data	Sujatha Das Gollapalli, Cornelia Caragea, Prasenjit Mitra, C. Lee Giles	As an alternative to obtaining datasets to retrain the classifier for the new content, we propose to use effectively unlimited amounts of unlabeled data readily available from these websites in a co-training scenario.
42	Google+ or Google-?: dissecting the evolution of the new OSN in its first year	Roberto Gonzalez, Ruben Cuevas, Reza Motamedi, Reza Rejaie, Angel Cuevas	This paper tackles the above question by presenting a detailed characterization of G+ based on large scale measurements.
43	Probabilistic group recommendation via information matching	Jagadeesh Gorla, Neal Lathia, Stephen Robertson, Jun Wang	Research to date in this domain has proposed two approaches: computing recommendations for the group by merging any members’ ratings into a single profile, or computing ranked recommendations for each individual that are then merged via a range of heuristics.
44	WTF: the who to follow service at Twitter	Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, Reza Zadeh	We describe and evaluate a few graph recommendation algorithms implemented in Cassovary, including a novel approach based on a combination of random walks and SALSA.
45	Mining expertise and interests from social media	Ido Guy, Uri Avraham, David Carmel, Sigalit Ur, Michal Jacovi, Inbal Ronen	In this work, we provide an extensive study that explores the use of social media to infer expertise within a large global organization.
46	Measuring personalization of web search	Aniko Hannak, Piotr Sapiezynski, Arash Molavi Kakhki, Balachander Krishnamurthy, David Lazer, Alan Mislove, Christo Wilson	In light of this situation, we make three contributions.
47	Estimating clustering coefficients and size of social networks via random walk	Stephen J. Hardiman, Liran Katzir	In this work, we provide efficient algorithms for estimating these measures which (1) assume no prior knowledge about the network; and (2) access the network using only the publicly available interface.
48	Exploiting annotations for the rapid development of collaborative web applications	Matthias Heinrich, Franz Josef Grüneberger, Thomas Springer, Martin Gaedke	To ease the development of collaborative web applications, we propose a set of source code annotations representing a lightweight mechanism to introduce concurrency control services into mature web frameworks.
49	Web usage mining with semantic analysis	Laura Hollink, Peter Mika, Roi Blanco	In our work, we aim to characterize websites in terms of the semantics of the queries that lead to them by linking queries to large knowledge bases on the Web.
50	Organizational overlap on social networks and its applications	Cho-Jui Hsieh, Mitul Tiwari, Deepak Agarwal, Xinyi (Lisa) Huang, Sam Shah	In this paper, we address the problem of computing edge affinity between two users on a social network, based on the users belonging to organizations such as companies, schools, and online groups.
51	Space-efficient data structures for Top-k completion	Bo-June (Paul) Hsu, Giuseppe Ottaviano	In this paper, we focus on the case where the string set is so large that compression is needed to fit the data structure in memory.
52	Personalized recommendation via cross-domain triadic factorization	Liang Hu, Jian Cao, Guandong Xu, Longbing Cao, Zhiping Gu, Can Zhu	In this paper, we propose a generalized Cross Domain Triadic Factorization (CDTF) model over the triadic relation user-item-domain, which can better capture the interactions between domain-specific user factors and item factors.
53	Unsupervised sentiment analysis with emotional signals	Xia Hu, Jiliang Tang, Huiji Gao, Huan Liu	Inspired by the wide availability of emotional signals in social media, we propose to study the problem of unsupervised sentiment analysis with emotional signals.
54	An analysis of socware cascades in online social networks	Ting-Kai Huang, Md Sazzadur Rahman, Harsha V. Madhyastha, Michalis Faloutsos, Bruno Ribeiro	In this paper, we analyze data from the walls of roughly 3 million Facebook users over five months, with the goal of developing a better understanding of socware cascades.
55	Measurement and analysis of child pornography trafficking on P2P networks	Ryan Hurley, Swagatika Prusty, Hamed Soroush, Robert J. Walls, Jeannie Albrecht, Emmanuel Cecchet, Brian Neil Levine, Marc Liberatore, Brian Lynn, Janis Wolak	In this paper, we examine observations of peers sharing known CP on the eMule and Gnutella networks, which were collected by law enforcement using forensic tools that we developed.
56	HeteroMF: recommendation in heterogeneous information networks using context dependent factor models	Mohsen Jamali, Laks Lakshmanan	In this paper, we propose a context-dependent matrix factorization model, HeteroMF, that considers a general latent factor for entities of every entity type and context-dependent latent factors for every context in which the entities are involved.
57	Interactive exploratory search for multi page search results	Xiaoran Jin, Marc Sloan, Jun Wang	Instead, we propose a new feedback scheme that makes use of existing UIs and does not alter user’s browsing behaviour; to maximise retrieval performance over multiple result pages, we propose a novel retrieval optimisation framework and show that the optimal ranking policy should choose a diverse, exploratory ranking to display on the first page.
58	Spatio-temporal dynamics of online memes: a study of geo-tagged tweets	Krishna Y. Kamath, James Caverlee, Kyumin Lee, Zhiyuan Cheng	In our analysis, we (i) examine the impact of location, time, and distance on the adoption of hashtags, which is important for understanding meme diffusion and information propagation; (ii) examine the spatial propagation of hashtags through their focus, entropy, and spread; and (iii) present two methods that leverage the spatio-temporal propagation of hashtags to characterize locations.
59	Accountable key infrastructure (AKI): a proposal for a public-key validation infrastructure	Tiffany Hyun-Jin Kim, Lin-Shung Huang, Adrian Perrig, Collin Jackson, Virgil Gligor	In this paper, we propose AKI as a new public-key validation infrastructure, to reduce the level of trust in CAs.
60	DIGTOBI: a recommendation system for Digg articles using probabilistic modeling	Younghoon Kim, Yoonjae Park, Kyuseok Shim	In this paper, we propose DIGTOBI, a personalized recommendation system for Digg articles using a novel probabilistic modeling.
61	Understanding latency variations of black box services	Darja Krushevskaja, Mark Sandler	We propose a general framework for understanding performance of arbitrary black box services.
62	Diversified recommendation on graphs: pitfalls, measures, and algorithms	Onur Küçüktunç, Erik Saule, Kamer Kaya, Ümit V. Çatalyürek	In this paper, we show the deficiencies of popular evaluation techniques of diversification methods, and investigate multiple relevance and diversity measures to understand whether they have any correlations.
63	What is the added value of negative links in online social networks?	Jérôme Kunegis, Julia Preusse, Felix Schwagereit	To answer the question whether negative links have an added value for an online social network, we investigate the machine learning problem of predicting the negative links of such a network using only the positive links as a basis, with the idea that if this problem can be solved with high accuracy, then the "negative link" feature is redundant.
64	Voices of victory: a computational focus group framework for tracking opinion shift in real time	Yu-Ru Lin, Drew Margolin, Brian Keegan, David Lazer	We propose a novel approach to tame these sources of uncertainty through the introduction of "computational focus groups" to track opinion shifts in social media streams.
65	Rethinking the web as a personal archive	Siân E. Lindley, Catherine C. Marshall, Richard Banks, Abigail Sellen, Tim Regan	In the study reported here, we follow up on research that suggests a sense of ownership and control can be reinforced by federating online content as a virtual, single store; we do this by conducting interviews with 14 individuals about their Web-based content.
66	Expressive languages for selecting groups from graph-structured data	Vitaliy Liptchinsky, Benjamin Satzger, Rostyslav Zabolotnyi, Schahram Dustdar	We present an efficient algorithm for evaluating group queries in polynomial time from an input data graph.
67	Modeling/predicting the evolution trend of osn-based applications	Han Liu, Atif Nazir, Jinoo Joung, Chen-Nee Chuah	This paper presents a new continuous graph evolution model aimed to capture microscopic user-level behaviors that govern the growth of the UAG and collectively define the overall graph structure.
68	SoCo: a social network aided context-aware recommender system	Xin Liu, Karl Aberer	In this paper, we propose SoCo, a novel context-aware recommender system incorporating elaborately processed social network information.
69	Using stranger as sensors: temporal and geo-sensitive question answering via social media	Yefeng Liu, Todorka Alexandrova, Tatsuo Nakajima	We analyze the usage patterns and behaviors of the real-world end-users, discuss the lessons learned, and outline the future directions and possible applications that could be built on top of MoboQ.
70	Imagen: runtime migration of browser sessions for javascript web applications	James Teng Kin Lo, Eric Wohlstadter, Ali Mesbah	This paper presents our research into browser session migration for JavaScript-based web applications.
71	Gender swapping and user behaviors in online social games	Jing-Kai Lou, Kunwoo Park, Meeyoung Cha, Juyong Park, Chin-Laung Lei, Kuan-Ta Chen	In this paper we investigate the phenomenon of "gender swapping," which refers to players choosing avatars of genders opposite to their natural ones.
72	Mining structural hole spanners through information diffusion in social networks	Tiancheng Lou, Jie Tang	In this work, we precisely define the problem of mining top-k structural hole spanners in large-scale social networks and provide an objective (quality) function to formalize the problem.
73	On the evolution of the internet economic ecosystem	Richard T.B. Ma, John C.S. Lui, Vishal Misra	We propose a network aware, macroscopic model that captures the characteristics and interactions of the application and network providers, and show how it leads to a market equilibrium of the ecosystem.
74	Two years of short URLs internet measurement: security threats and countermeasures	Federico Maggi, Alessandro Frossi, Stefano Zanero, Gianluca Stringhini, Brett Stone-Gross, Christopher Kruegel, Giovanni Vigna	Despite short URLs are a significant, new security risk, in accordance with the reports resulting from the observation of the overall phishing and spamming activity, we found that only a relatively small fraction of users ever encountered malicious short URLs.
75	Know your personalization: learning topic level personalization in online services	Anirban Majumder, Nisheeth Shrivastava	In this paper, we capture OSP’s personalization for an user in a new data structure called the personalization vector (?)
76	Saving, reusing, and remixing web video: using attitudes and practices to reveal social norms	Catherine C. Marshall, Frank M. Shipman	Saving, reusing, and remixing web video: using attitudes and practices to reveal social norms
77	From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews	Julian John McAuley, Jure Leskovec	Thus our goal in this paper is to recommend products that a user will enjoy now, while acknowledging that their tastes may have changed over time, and may change again in the future.
78	The FLDA model for aspect-based opinion mining: addressing the cold start problem	Samaneh Moghaddam, Martin Ester	In this paper, we propose a probabilistic graphical model based on LDA, called Factorized LDA (FLDA), to address the cold start problem.
79	Iolaus: securing online content rating systems	Arash Molavi Kakhki, Chloe Kliman-Silver, Alan Mislove	In this paper, we present Iolaus, a system that leverages the underlying social network of online content rating systems to defend against such attacks.
80	On cognition, emotion, and interaction aspects of search tasks with different search intentions	Yashar Moshfeghi, Joemon M. Jose	Results show that we can learn a model that predicts the search task types with reasonable accuracy.
81	Ad impression forecasting for sponsored search	Abhirup Nath, Shibnath Mukherjee, Prateek Jain, Navin Goyal, Srivatsan Laxman	In this paper, we develop a generative model based approach that addresses these drawbacks.
82	Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts	Vidhya Navalpakkam, LaDawn Jentzsch, Rory Sayres, Sujith Ravi, Amr Ahmed, Alex Smola	We present a lab study on the effect of a rich informational panel to the right of the search result column, on eye and mouse behavior.
83	Understanding and decreasing the network footprint of catch-up tv	Gianfranco Nencioni, Nishanth Sastry, Jigna Chandaria, Jon Crowcroft	We find that catch-up has certain natural scaling properties compared to traditional TV: The on-demand nature spreads load over time, and users have much higher completion rates for content streams than previously reported.
84	Sorry, i don’t speak SPARQL: translating SPARQL queries into natural language	Axel-Cyrille Ngonga Ngomo, Lorenz Bühmann, Christina Unger, Jens Lehmann, Daniel Gerber	This paper addresses this drawback by presenting SPARQL2NL, a generic approach that allows verbalizing SPARQL queries, i.e., converting them into natural language.
85	Bitsquatting: exploiting bit-flips for fun, or profit?	Nick Nikiforakis, Steven Van Acker, Wannes Meert, Lieven Desmet, Frank Piessens, Wouter Joosen	In this paper, we report on a large-scale experiment, measuring the adoption of bitsquatting by the domain-squatting community through the tracking of registrations of bitsquatting domains targeting popular web sites over a 9-month period.
86	One-class collaborative filtering with random graphs	Ulrich Paquet, Noam Koenigstein	In this paper we present a novel Bayesian generative model for implicit collaborative filtering.
87	Latent credibility analysis	Jeff Pasternack, Dan Roth	We introduce a new approach to information credibility, Latent Credibility Analysis (LCA), constructing strongly principled, probabilistic models where the truth of each claim is a latent variable and the credibility of a source is captured by a set of model parameters.
88	Predicting group stability in online social networks	Akshay Patil, Juan Liu, Jie Gao	In this paper, we study two different types of social networks as exemplar platforms for modeling and predicting group stability dynamics.
89	Predictive web automation assistant for people with vision impairments	Yury Puzis, Yevgen Borodin, Rami Puzis, I.V. Ramakrishnan	In this paper, we propose a novel model-based approach that facilitates web automation without having to either record or replay macros.
90	Mining collective intelligence in diverse groups	Guo-Jun Qi, Charu C. Aggarwal, Jiawei Han, Thomas Huang	In order to address this issue, we propose a probabilistic model to jointly assess the reliability of sources and find the true data.
91	Trade area analysis using user generated mobile location data	Yan Qu, Jun Zhang	In this paper, we illustrate how User Generated Mobile Location Data (UGMLD) like Foursquare check-ins can be used in Trade Area Analysis (TAA) by introducing a new framework and corresponding analytic methods.
92	Psychological maps 2.0: a web engagement enterprise starting in London	Daniele Quercia, Joao Paulo Pesce, Virgilio Almeida, Jon Crowcroft	We build a web game that puts the recognizability of London’s streets to the test. We collect data from 2,255 participants (one order of magnitude a larger sample) and build a recognizability map of London based on their responses.
93	Towards realistic team formation in social networks based on densest subgraphs	Syama Sundar Rangapuram, Thomas Bühler, Matthias Hein	The goal of this paper is to consider the team formation problem in a realistic setting and present a novel formulation based on densest subgraphs.
94	Efficient community detection in large networks using content and links	Yiye Ruan, David Fuhry, Srinivasan Parthasarathy	In this paper we discuss a very simple approach of combining content and link information in graph structures for the purpose of community discovery, a fundamental task in network analysis.
95	Learning joint query interpretation and response ranking	Uma Sawant, Soumen Chakrabarti	We propose two new, natural formulations for joint query interpretation and response ranking that exploit bidirectional flow of information between the knowledge base and the corpus.
96	A model for green design of online news media services	Daniel Schien, Paul Shabajee, Stephen G. Wood, Chris Preist	In this work we describe a new method which combines models of energy consumption during the use of digital media with models of the behavior of the audience.
97	Potential networks, contagious communities, and understanding social network structure	Grant Schoenebeck	In this paper we study how the network of agents adopting a particular technology relates to the structure of the underlying network over which the technology adoption spreads.
98	Do social explanations work?: studying and modeling the effects of social explanations in recommender systems	Amit Sharma, Dan Cosley	Based on these insights, we present a generative probabilistic model that explains the interplay between explanations and background information on music preferences, and how that leads to a final likelihood rating for an artist.
99	Question answering on interlinked data	Saeedeh Shekarpour, Axel-Cyrille Ngonga Ngomo, Sören Auer	We present a question answering system, which transforms user supplied queries (i.e. natural language sentences or keywords) into conjunctive SPARQL queries over a set of interlinked data sources.
100	Pricing mechanisms for crowdsourcing markets	Yaron Singer, Manas Mittal	In this paper, we introduce a framework for designing mechanisms with provable guarantees in crowdsourcing markets.
101	Truthful incentives in crowdsourcing tasks using regret minimization mechanisms	Adish Singla, Andreas Krause	In this paper, we address these questions and present mechanisms using the approach of regret minimization in online learning.
102	A predictive model for advertiser value-per-click in sponsored search	Eric Sodomka, Sébastien Lahaie, Dustin Hillard	In this paper we propose an approach to keyword value prediction that draws on advertiser bidding behavior across the terms and campaigns in an account.
103	I know the shortened URLs you clicked on Twitter: inference attack using public click analytics and Twitter metadata	Jonghyuk Song, Sangho Lee, Jong Kim	In this paper, we propose a practical attack technique that can infer who clicks what shortened URLs on Twitter.
104	Exploring and exploiting user search behavior on mobile and tablet devices to improve search relevance	Yang Song, Hao Ma, Hongning Wang, Kuansan Wang	In this paper, we present a log-based study on user search behavior comparisons on three different platforms: desktop, mobile and tablet.
105	Evaluating and predicting user engagement change with degraded search relevance	Yang Song, Xiaolin Shi, Xin Fu	We believe that insights from this study can be leveraged by search engine companies to detect and intervene search relevance degradation and to prevent long term user engagement drop.
106	Data-Fu: a language and an interpreter for interaction with read/write linked data	Steffen Stadtmüller, Sebastian Speiser, Andreas Harth, Rudi Studer	For declaratively specifying interactions between web resources we introduce Data-Fu, a lightweight declarative rule language with state transition systems as formal grounding.
107	NIFTY: a system for large scale information flow tracking and clustering	Caroline Suen, Sandy Huang, Chantat Eksombatchai, Rok Sosic, Jure Leskovec	We describe the News Information Flow Tracking, Yay!
108	When relevance is not enough: promoting diversity and freshness in personalized question recommendation	Idan Szpektor, Yoelle Maarek, Dan Pelleg	We found that those drawing-board requirements fail to capture user’s interests.
109	Mining acronym expansions and their meanings using query click log	Bilyana Taneva, Tao Cheng, Kaushik Chakrabarti, Yeye He	We present a novel, end-to-end solution that addresses the above challenges.
110	Groundhog day: near-duplicate detection on Twitter	Ke Tao, Fabian Abel, Claudia Hauff, Geert-Jan Houben, Ujwal Gadiraju	We investigate the problem of near-duplicate detection on Twitter and introduce a framework that analyzes the tweets by comparing (i) syntactical characteristics, (ii) semantic similarity, and (iii) contextual information.
111	Uncovering locally characterizing regions within geotagged data	Bart Thomee, Adam Rae	We propose a novel algorithm for uncovering the colloquial boundaries of locally characterizing regions present in collections of labeled geospatial data.
112	Spectral analysis of communication networks using Dirichlet eigenvalues	Alexander Tsiatas, Iraj Saniee, Onuttom Narayan, Matthew Andrews	Spectral methods provide effective means to estimate the smallest Cheeger ratio via the spectral gap of the graph Laplacian.
113	Subgraph frequencies: mapping the empirical and extremal geography of large graph collections	Johan Ugander, Lars Backstrom, Jon Kleinberg	In this work, we draw on the theory of graph homomorphisms to formulate and analyze such a representation, based on computing the frequencies of small induced subgraphs within each graph.
114	The self-feeding process: a unifying model for communication dynamics in the web	Pedro Olmo S. Vaz de Melo, Christos Faloutsos, Renato Assunção, Antonio Loureiro	We show here that, surprisingly, both approaches are correct, being corner cases of the proposed Self-Feeding Process (SFP).
115	Google+Ripples: a native visualization of information flow	Fernanda Viégas, Martin Wattenberg, Jack Hebert, Geoffrey Borggaard, Alison Cichowlas, Jonathan Feinberg, Jon Orwant, Christopher Wren	We describe the visualization technique, which is a new mix of node-and-link and circular treemap metaphors.
116	Whom to mention: expand the diffusion of tweets by @ recommendation on micro-blogging systems	Beidou Wang, Can Wang, Jiajun Bu, Chun Chen, Wei Vivian Zhang, Deng Cai, Xiaofei He	In this paper, whom-to-mention is formulated as a ranking problem and we try to address several new challenges which are not well studied in the traditional information retrieval tasks.
117	Wisdom in the social crowd: an analysis of quora	Gang Wang, Konark Gill, Manish Mohanlal, Haitao Zheng, Ben Y. Zhao	In this paper, we present results of a detailed analysis of Quora using measurements.
118	Learning to extract cross-session search tasks	Hongning Wang, Yang Song, Ming-Wei Chang, Xiaodong He, Ryen W. White, Wei Chu	In this work, we target the identification of long-term, or cross-session, search tasks (transcending session boundaries) by investigating inter-query dependencies learned from users’ searching behaviors.
119	Content-aware click modeling	Hongning Wang, ChengXiang Zhai, Anlei Dong, Yi Chang	In this work, we proposed a novel Bayesian Sequential State model for modeling the user click behaviors, where the document content and dependencies among the sequential click events within a query are characterized by a set of descriptive features via a probabilistic graphical model.
120	Is it time for a career switch?	Jian Wang, Yi Zhang, Christian Posse, Anmol Bhasin	Is it time for a career switch?
121	From cookies to cooks: insights on dietary patterns via analysis of web usage logs	Robert West, Ryen W. White, Eric Horvitz	In this preliminary study, we focus on patterns of sodium identified in recipes over time and patterns of admission for congestive heart failure, a chronic illness that can be exacerbated by increases in sodium intake.
122	Enhancing personalized search by mining and modeling task behavior	Ryen W. White, Wei Chu, Ahmed Hassan, Xiaodong He, Yang Song, Hongning Wang	We describe a method whereby we mine historic search-engine logs to find other users performing similar tasks to the current user and leverage their on-task behavior to identify Web pages to promote in the current ranking.
123	Inferring dependency constraints on parameters for web services	Qian Wu, Ling Wu, Guangtai Liang, Qianxiang Wang, Tao Xie, Hong Mei	To address this issue, we propose a novel approach, called INDICATOR, to automatically infer dependency constraints on parameters for web services, via a hybrid analysis of heterogeneous web service artifacts, including the service documentation, the service SDKs, and the web services themselves.
124	Predicting advertiser bidding behaviors in sponsored search by rationality modeling	Haifeng Xu, Bin Gao, Diyi Yang, Tie-Yan Liu	In this paper, we explicitly model these limitations in the rationality of advertisers, and build a probabilistic advertiser behavior model from the perspective of a search engine.
125	A biterm topic model for short texts	Xiaohui Yan, Jiafeng Guo, Yanyan Lan, Xueqi Cheng	In this paper, we propose a novel way for modeling topics in short texts, referred as biterm topic model (BTM).
126	Unified entity search in social media community	Ting Yao, Yuan Liu, Chong-Wah Ngo, Tao Mei	To infer the strength of intra-relations, we propose a circular propagation scheme, which reinforces the mutual exchange of information across different entity types in a cyclic manner.
127	MATRI: a multi-aspect and transitive trust inference model	Yuan Yao, Hanghang Tong, Xifeng Yan, Feng Xu, Jian Lu	In this paper, we propose a multi-aspect trust inference model by exploring an equally important property of trust, i.e., the multi-aspect property.
128	Predicting positive and negative links in signed social networks by transfer learning	Jihang Ye, Hong Cheng, Zhe Zhu, Minghua Chen	Different from a large body of research on social networks that has focused almost exclusively on positive relationships, we study signed social networks with both positive and negative links.
129	Sparse online topic models	Aonan Zhang, Jun Zhu, Bo Zhang	In this paper, we present a sparse online topic model, which directly controls the sparsity of latent semantic patterns by imposing sparsity-inducing regularization and learns the topical dictionary by an online algorithm.
130	TopRec: domain-specific recommendation through community topic mining in social network	Xi Zhang, Jian Cheng, Ting Yuan, Biao Niu, Hanqing Lu	In this paper, we propose a unified framework, TopRec, which detects topical communities to construct interpretable domains for domain-specific collaborative filtering.
131	Localized matrix factorization for recommendation based on matrix block diagonal forms	Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma, Shi Feng	In this paper, we present the Localized Matrix Factorization (LMF) framework, which attempts to meet the challenges of sparsity and scalability by factorizing Block Diagonal Form (BDF) matrices.
132	Predicting purchase behaviors from social media	Yongzheng Zhang, Marco Pennacchiotti	This paper presents a system for predicting a user’s purchase behaviors on e-commerce websites from the user’s social media profile.
133	Anatomy of a web-scale resale market: a data mining approach	Yuchen Zhao, Neel Sundaresan, Zeqian Shen, Philip S. Yu	In this paper, we study an instance of such markets that affords interesting data at large scale for mining purposes to understand the properties and patterns of this online market.As part of knowledge discovery of such a market, we first formally propose criteria to reveal unseen resale behaviors by elastic matching identification (EMI) based on the account transfer and item similarity properties of transactions.
134	Questions about questions: an empirical analysis of information needs on Twitter	Zhe Zhao, Qiaozhu Mei	In this study, we take the initiative to extract and analyze information needs from billions of online conversations collected from Twitter.
135	Which vertical search engines are relevant?	Ke Zhou, Ronan Cummins, Mounia Lalmas, Joemon M. Jose	To address this, we present a formal analysis and a set of extensive user studies to investigate the effects of various assumptions made for assessing query vertical relevance.
136	Making the most of your triple store: query answering in OWL 2 using an RL reasoner	Yujiao Zhou, Bernardo Cuenca Grau, Ian Horrocks, Zhe Wu, Jay Banerjee	In this paper, we propose novel techniques that allow us (in many cases) to compute exact query answers using an off-the-shelf RL reasoner, even when the ontology is outside the RL profile.
137	Security implications of password discretization for click-based graphical passwords	Bin B. Zhu, Dongchen Wei, Maowei Yang, Jeff Yan	In this paper, we show for the first time that two representative discretization schemes leak a significant amount of password information, undermining the security of such graphical passwords.