OpenRaiser/Intern-Atlas huggingface dataset:
ProFoUnd: program-analysis-based form understanding
Authors: Michael Benedikt, Tim Furche, Andreas Savvides, Pierre Senellart
Venue: WWW
Year: 2012

An important feature of web search interfaces are the restrictions enforced on input values - those reflecting either the semantics of the data or requirements specific to the interface. Both integrity constraints and "access restrictions" can be of great use to web exploration tools. We demonstrate here a novel technique for discovering constraints that requires no form submissions whatsoever. We work via statically analyzing the JavaScript client-side code used to enforce the constraints, when such code is available. We combine custom recognizers for JavaScript functions relevant to constraint checking with a generic program analysis layer. Integrated with a web browser, our system shows the constraints detected on accessed web forms, and allows a user to see the corresponding JavaScript code fragment.
Multi-application profile updates propagation: a semantic layer to improve mapping between applications
Authors: Nadia Bennani, Max Chevalier, Elöd Egyed-Zsigmond, Gilles Hubert, Marco Viviani
Venue: WWW
Year: 2012

In the field of multi-application personalization, several techniques have been proposed to support user modeling for user data management across different applications. Many of them are based on data reconciliation techniques often implying the concepts of static ontologies and generic user data models. None of them have sufficiently investigated two main issues related to user modeling: (1) profile definition in order to allow every application to build their own view of users while promoting the sharing of these profiles and (2) profile evolution over time in order to avoid data inconsistency and the subsequent loss of income for web-site users and companies. In this paper, we conduct work and propose separated solutions for every issue. We propose a flexible user modeling system, not imposing any fixed user model whom different applications should conform to, but based on the concept of mapping among applications (and mapping functions among their user attributes). We focus in particular on the management of user profile data propagation, as a way to reduce the amount of inconsistent user profile information over several applications. A second goal of this paper is to illustrate, in this context, the benefit obtained by the integration of a Semantic Layer that can help application designers to automatically identify potential user attribute mappings between applications. This paper so illustrates a work-in-progress work where two complementary approaches are integrated to improve a main goal: managing multi-application user profiles in a semi-automatic manner. Copyright is held by the International World Wide Web Conference Committee (IW3C2).
Group recommendations via multi-armed bandits
Authors: José Bento, Stratis Ioannidis, S. Muthukrishnan, Jinyun Yan
Venue: WWW
Year: 2012

We study recommendations for persistent groups that repeatedly engage in a joint activity. We approach this as a multi-arm bandit problem. We design a recommendation policy and show it has logarithmic regret. Our analysis also shows that regret depends linearly on d, the size of the underlying persistent group. We evaluate our policy on movie recommendations over the MovieLens and MoviePilot datasets.
A social network for video annotation and discovery based on semantic profiling
Authors: Marco Bertini, Alberto Del Bimbo, Andrea Ferracani, Daniele Pezzatini
Venue: WWW
Year: 2012

This paper presents a system for the social annotation and discovery of videos based on social networks and social knowledge. The system, developed as a web application, allows users to comment and annotate, manually and automatically, video frames and scenes enriching their content with tags, references to Facebook users and pages and Wikipedia resources. These annotations are used to semantically model the interests and the folksonomy of each user and resource in the network, and to suggest to users new resources, Facebook friends and videos whose content is related to their interests. A screencast showing an example of these functionalities is publicly available at:http://vimeo.com/miccunifi/facetube
Branded with a scarlet "C": cheaters in a gaming social network
Authors: Jeremy Blackburn, Ramanuja Simha, Nicolas Kourtellis, Xiang Zuo, Matei Ripeanu, John Skvoretz, Adriana Iamnitchi
Venue: WWW
Year: 2012

Online gaming is a multi-billion dollar industry that entertains a large, global population. One unfortunate phenomenon, however, poisons the competition and the fun: cheating. The costs of cheating span from industry-supported expenditures to detect and limit cheating, to victims' monetary losses due to cyber crime. This paper studies cheaters in the Steam Community, an online social network built on top of the world's dominant digital game delivery platform. We collected information about more than 12 million gamers connected in a global social network, of which more than 700 thousand have their profiles flagged as cheaters. We also collected in-game interaction data of over 10 thousand players from a popular multiplayer gaming server. We show that cheaters are well embedded in the social and interaction networks: their network position is largely indistinguishable from that of fair players. We observe that the cheating behavior appears to spread through a social mechanism: the presence and the number of cheater friends of a fair player is correlated with the likelihood of her becoming a cheater in the future. Also, we observe that there is a social penalty involved with being labeled as a cheater: cheaters are likely to switch to more restrictive privacy settings once they are tagged and they lose more friends than fair players. Finally, we observe that the number of cheaters is not correlated with the geographical, real-world population density, or with the local popularity of the Steam Community.
TwitterEcho: a distributed focused crawler to support open research with twitter data
Authors: Matko Bosnjak, Eduardo Oliveira, José Martins, Eduarda Mendes Rodrigues, Luís Sarmento
Venue: WWW
Year: 2012

Modern social network analysis relies on vast quantities of data to infer new knowledge about human relations and communication. In this paper we describe TwitterEcho, an open source Twitter crawler for supporting this kind of research, which is characterized by a modular distributed architecture. Our crawler enables researchers to continuously collect data from particular user communities, while respecting Twitter's imposed limits. We present the core modules of the crawling server, some of which were specifically designed to focus the crawl on the Portuguese Twittosphere. Additional modules can be easily implemented, thus changing the focus to a different community. Our evaluation of the system shows high crawling performance and coverage.
GovWILD: integrating open government data for transparency
Authors: Christoph Böhm, Markus Freitag, Arvid Heise, Claudia Lehmann, Andrina Mascher, Felix Naumann, Vuk Ercegovac, Mauricio A. Hernández, Peter Haase, Michael Schmidt
Venue: WWW
Year: 2012

Many government organizations publish a variety of data on the web to enable transparency, foster applications, and to satisfy legal obligations. Data content, format, structure, and quality vary widely, even in cases where the data is published using the wide-spread linked data principles. Yet within this data and their integration lies much value: We demonstrate GovWILD, a web-based prototype that integrates and cleanses Open Government Data at a large scale. Apart from the web-based interface that presents a use case of the created dataset at govwild.org, we provide all integrated data as a download. This data can be used to answer questions about politicians, companies, and government funding.
Answering search queries with CrowdSearcher
Authors: Alessandro Bozzon, Marco Brambilla, Stefano Ceri
Venue: WWW
Year: 2012

Web users are increasingly relying on social interaction to complete and validate the results of their search activities. While search systems are superior machines to get world-wide information, the opinions collected within friends and expert/local communities can ultimately determine our decisions: human curiosity and creativity is often capable of going much beyond the capabilities of search systems in scouting "interesting" results, or suggesting new, unexpected search directions. Such personalized interaction occurs in most times aside of the search systems and processes, possibly instrumented and mediated by a social network; when such interaction is completed and users resort to the use of search systems, they do it through new queries, loosely related to the previous search or to the social interaction. In this paper we propose CrowdSearcher, a novel search paradigm that embodies crowds as first-class sources for the information seeking process. CrowdSearcher aims at filling the gap between generalized search systems, which operate upon world-wide information - including facts and recommendations as crawled and indexed by computerized systems - with social systems, capable of interacting with real people, in real time, to capture their opinions, suggestions, emotions. The technical contribution of this paper is the discussion of a model and architecture for integrating computerized search with human interaction, by showing how search systems can drive and encapsulate social systems. In particular we show how social platforms, such as Facebook, LinkedIn and Twitter, can be used for crowdsourcing search-related tasks; we demonstrate our approach with several prototypes and we report on our experiment upon real user communities.
A revenue sharing mechanism for federated search and advertising
Authors: Marco Brambilla, Sofia Ceppi, Nicola Gatti, Enrico H. Gerding
Venue: WWW
Year: 2012

Federated search engines combine search results from two or more (general--purpose or domain--specific) content providers. They enable complex searches (e.g., complete vacation planning) or more reliable results by allowing users to receive high quality results from a variety of sources. We propose a new revenue sharing mechanism for federated search engines, considering different actors involved in the search results generation (i.e., content providers, advertising providers, hybrid content+advertising providers, and content integrators). We extend the existing sponsored search auctions by supporting heterogeneous participants and redistribution of monetary values to the different actors, while maintaining flexibility in the payment scheme.
Combining social web and BPM for improving enterprise performances: the BPM4People approach to social BPM
Authors: Marco Brambilla, Piero Fraternali, Carmen Karina Vaca Ruiz
Venue: WWW
Year: 2012

Social BPM fuses business process management practices with social networking applications, with the aim of enhancing the enterprise performance by means of a controlled participation of external stakeholders to process design and enactment. This project-centered demonstration paper proposes a model-driven approach to participatory and social enactment of business processes. The approach consists of defining a specific notation for describing Social BPM behaviors (defined as a BPMN 2.0 extension), a methodology, and a technical framework that allows enterprises to implement of social processes as Web applications integrated with public or private Web social networks. The presented work is performed within the BPM4People SME Capacities project
Efficient multi-view maintenance in the social semantic web
Authors: Matthias Broecheler, Andrea Pugliese, V. S. Subrahmanian
Venue: WWW
Year: 2012

The Social Semantic Web (SSW) refers to the mix of RDF data in web content, and social network data associated with those who posted that content. Applications to monitor the SSW 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. Such 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 paper, we develop the concept of SSW view servers in which all of these types of applications can be simultaneously monitored from such servers. The patterns of interest are views. 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. We develop a very fast MultiView algorithm that scalably and efficiently maintains multiple subgraph views. 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 real-world SSW databases with up to 540M edges.
Bimodal invitation-navigation fair bets model for authority identification in a social network
Authors: Suratna Budalakoti, Ron Bekkerman
Venue: WWW
Year: 2012

We consider the problem of identifying the most respected, authoritative members of a large-scale online social network (OSN) by constructing a global ranked list of its members. The problem is distinct from the problem of identifying influencers: we are interested in identifying members who are influential in the real world, even when not necessarily so on the OSN. We focus on two sources for information about user authority: (a) invitations to connect, which are usually sent to people whom the inviter respects, and (b) members' browsing behavior, as profiles of more important people are viewed more often than others'. We construct two directed graphs over the same set of nodes (representing member profiles): the invitation graph and the navigation graph respectively. We show that the standard PageRank algorithm, a baseline in web page ranking, is not effective in people ranking, and develop a social capital based model, called the fair bets model, as a viable solution. We then propose a novel approach, called bimodal fair bets, for combining information from two (or more) endorsement graphs drawn from the same OSN, by simultaneously using the authority scores of nodes in one graph to inform the other, and vice versa, in a mutually reinforcing fashion. We evaluate the ranking results on the LinkedIn social network using this model, where members who have Wikipedia profiles are assumed to be authoritative. Experimental results show that our approach outperforms the baseline approach by a large margin.
Context-sensitive business process support based on emails
Authors: Thomas Burkhart, Dirk Werth, Peter Loos
Venue: WWW
Year: 2012

In many companies, a majority of business processes take place via email communication. Large enterprises have the possibility to operate enterprise systems for a successful business process management. However, these systems are not appropriate for SMEs, which are the most common enterprise type in Europe. Thus, the European research project Commius addresses the special needs of SMEs and characteristics of email communication, namely highly flexibility and unstructuredness. Commius turns the existing email-system into a structured process management framework. Each incoming email is autonomously matched to the corresponding business process and enhanced by proactive annotations. These context-sensitive annotations include recommendations for the most suitable following process steps. An underlying, self-adjusting recommendation model ensures most appropriate recommendations by observing the actual user behavior. This implies that the proposed process course is in no way obligatory. To provide a high degree of flexibility, any deviation from the given process structure is allowed.
SessionJuggler: secure web login from an untrusted terminal using session hijacking
Authors: Elie Bursztein, Chinmay Soman, Dan Boneh, John C. Mitchell
Venue: WWW
Year: 2012

We use modern features of web browsers to develop a secure login system from an untrusted terminal. The system, called Session Juggler, requires no server-side changes and no special software on the terminal beyond a modern web browser. This important property makes adoption much easier than with previous proposals. With Session Juggler users never enter their long term credential on the untrusted terminal. Instead, users log in to a web site using a smartphone app and then transfer the entire session, including cookies and all other session state, to the untrusted terminal. We show that Session Juggler works on all the Alexa top 100 sites except eight. Of those eight, five failures were due to the site enforcing IP session binding. We also show that Session Juggler works flawlessly with Facebook connect. Beyond login, Session Juggler also provides a secure logout mechanism where the trusted phone is used to kill the session. To validate the session juggling concept we conducted a number of web site surveys that are of independent interest. First, we survey how web sites bind a session token to a specific device and show that most use fairly basic techniques that are easily defeated. Second, we survey how web sites handle logout and show that many popular sites surprisingly do not properly handle logout requests.
Enriching temporal query understanding through date identification: how to tag implicit temporal queries?
Authors: Ricardo Campos, Gaël Dias, Alípio Mário Jorge, Celia Nunes
Venue: WWW
Year: 2012

Generically, search engines fail to understand the user's temporal intents when expressed as implicit temporal queries. This causes the retrieval of less relevant information and prevents users from being aware of the possible temporal dimension of the query results. In this paper, we aim to develop a language-independent model that tackles the temporal dimensions of a query and identifies its most relevant time periods. For this purpose, we propose a temporal similarity measure capable of associating a relevant date(s) to a given query and filtering out irrelevant ones. Our approach is based on the exploitation of temporal information from web content, particularly within the set of k-top retrieved web snippets returned in response to a query. We particularly focus on extracting years, which are a kind of temporal information that often appears in this type of collection. We evaluate our methodology using a set of real-world text temporal queries, which are clear concepts (i.e. querie
News comments generation via mining microblogs
Authors: Xuezhi Cao, Kailong Chen, Rui Long, Guoqing Zheng, Yong Yu
Venue: WWW
Year: 2012

Microblogging websites such as Twitter and Chinese Sina Weibo contain large amounts of microblogs posted by users. Many of these microblogs are highly sensitive to the important real-world events and correlated to the news events. Thus, microblogs from these websites can be collected as comments for the news to reveal the opinions and attitude towards the news event among large number of users. In this paper, we present a framework to automatically collect relevant microblogs from microblogging websites to generate comments for popular news on news websites.
BlueFinder: estimate where a beach photo was taken
Authors: Liangliang Cao, John R. Smith, Zhen Wen, Zhijun Yin, Xin Jin, Jiawei Han
Venue: WWW
Year: 2012

This paper describes a system to estimate geographical locations for beach photos. We develop an iterative method that not only trains visual classifiers but also discovers geographical clusters for beach regions. The results show that it is possible to recognize different beaches using visual information with reasonable accuracy, and our system works 27 times better than random guess for the geographical localization task.
MobiMash: end user development for mobile mashups
Authors: Cinzia Cappiello, Maristella Matera, Matteo Picozzi, Alessandro Caio, Mariano Tomas Guevara
Venue: WWW
Year: 2012

The adoption of adequate tools, oriented towards the End User Development (EUD), can promote mobile mashups as "democratic" tools, able to accommodate the long tail of users' specific needs. We introduce MobiMash, a novel approach and a platform for the construction of mobile mashups, characterized by a lightweight composition paradigm, mainly guided by the notion of visual templates. The composition paradigm generates an application schema that is based on a domain specific language addressing dimensions for data integration and service orchestration, and that guides at run- time the dynamic instantiation of the final mobile app.
Entity oriented search and exploration for cultural heritage collections: the EU cultura project
Authors: David Carmel, Naama Zwerdling, Sivan Yogev
Venue: WWW
Year: 2012

In this paper we describe an entity oriented search and exploration system that we are developing for the EU Cultura project.
Automated community detection on social networks: useful? efficient? asking the users
Authors: Rémy Cazabet, Maud Leguistin, Frédéric Amblard
Venue: WWW
Year: 2012

In most online social networks, with the increasing number of users and content, the problem of contact filtering becomes more and more present. The recent introduction of such features in online social networks -- for instance, Circles in Google+ or Facebook Smart lists -- shows that it is a problem they are confronted to. In this paper, we explore this question through multidisciplinary aspects. First, we discuss about this issue of groups management in the context of social networks. Then, we present several techniques from the state of the art to automatically find meaningful groups of contacts in a user's contact list. Finally, we asked Facebook users to evaluate these solutions on their own Facebook network, both to compare the solutions among themselves and to assess how pertinent the best ones are according to them. The conclusions of this study is that a network analysis approach can strongly improve the efficiency of an automated detection of groups on networks, which could be used, combined with profile data extraction, to design intelligent management of groups of contacts.
Compressed data structures for annotated web search
Authors: Soumen Chakrabarti, Sasidhar Kasturi, Bharath Balakrishnan, Ganesh Ramakrishnan, Rohit Saraf
Venue: WWW
Year: 2012

Entity relationship search at Web scale depends on adding dozens of entity annotations to each of billions of crawled pages and indexing the annotations at rates comparable to regular text indexing. Even small entity search benchmarks from TREC and INEX suggest that the entity catalog support thousands of entity types and tens to hundreds of millions of entities. The above targets raise many challenges, major ones being the design of highly compressed data structures in RAM for spotting and disambiguating entity mentions, and highly compressed disk-based annotation indices. These data structures cannot be readily built upon standard inverted indices. Here we present a Web scale entity annotator and annotation index. Using a new workload-sensitive compressed multilevel map, we fit statistical disambiguation models for millions of entities within 1.15GB of RAM, and spend about 0.6 core-milliseconds per disambiguation. In contrast, DBPedia Spotlight spends 158 milliseconds, Wikipedia Miner spends 21 milliseconds, and Zemanta spends 9.5 milliseconds. Our annotation indices use ideas from vertical databases to reduce storage by 30%. On 40x8 cores with 40x3 disk spindles, we can annotate and index, in about a day, a billion Web pages with two million entities and 200,000 types from Wikipedia. Index decompression and scan speed are comparable to MG4J.