OpenRaiser/Intern-Atlas huggingface dataset:
Identifying overlapping communities in folksonomies or tripartite hypergraphs
Authors: Saptarshi Ghosh, Pushkar Kane, Niloy Ganguly
Venue: WWW
Year: 2011

Online folksonomies are modeled as tripartite hypergraphs, and detecting communities from such networks is a challenging and well-studied problem. However, almost every existing algorithm known to us for community detection in hypergraphs assign unique communities to nodes, whereas in reality, nodes in folksonomies belong to multiple overlapping communities e.g. users have multiple topical interests, and the same resource is often tagged with semantically different tags. In this paper, we propose an algorithm to detect overlapping communities in folksonomies by customizing a recently proposed edge-clustering algorithm (that is originally for traditional graphs) for use on hypergraphs.
Spammers' networks within online social networks: a case-study on Twitter
Authors: Saptarshi Ghosh, Gautam Korlam, Niloy Ganguly
Venue: WWW
Year: 2011

We analyze the strategies employed by contemporary spammers in Online Social Networks (OSNs) by identifying a set of spam-accounts in Twitter and monitoring their link-creation strategies. Our analysis reveals that spammers adopt intelligent 'collaborative' strategies of link-formation to avoid detection and to increase the reach of their generated spam, such as forming 'spam-farms' and creating large number of links with targeted legitimate users. The observations are verified through the analysis of a giant 'spam-farm' embedded within the Twitter OSN.
Networked hierarchies for web directories
Authors: Nazli Goharian, Saket S. R. Mengle
Venue: WWW
Year: 2011

The hierarchical nature of existing Web directories, ontologies, and folksonomies, are known to provide meaningful information that guide users and applications. We hypothesize that such hierarchical structures provide richer information if they are further enriched by incorporating additional links besides parents, and siblings, namely, between non-sibling nodes. We call such structure a networked hierarchy. Our empirical results indicate that such a networked hierarchy introduces interesting links between nodes (non-sibling) that otherwise in a hierarchical structure are not evident.
Adaptive policies for selecting groupon style chunked reward ads in a stochastic knapsack framework
Authors: Michael Grabchak, Narayan L. Bhamidipati, Rushi Bhatt, Dinesh Garg
Venue: WWW
Year: 2011

Stochastic knapsack problems deal with selecting items with potentially random sizes and rewards so as to maximize the total reward while satisfying certain capacity constraints. A novel variant of this problem, where items are worthless unless collected in bundles, is introduced here. This setup is similar to the Groupon model, where a deal is off unless a minimum number of users sign up for it. Since the optimal algorithm to solve this problem is not practical, several adaptive greedy approaches with reasonable time and memory requirements are studied in detail - theoretically, as well as, experimentally. Worst case performance guarantees are provided for some of these greedy algorithms, while results of experimental evaluation demonstrate that they are much closer to optimal than what the theoretical bounds suggest. Applications include optimizing for online advertising pricing models where advertisers pay only when certain goals, in terms of clicks or conversions, are met. We perform extensive experiments for the situation where there are between two and five ads. For typical ad conversion rates, the greedy policy of selecting items having the highest individual expected reward obtains a value within 5% of optimal over 95% of the time for a wide selection of parameters.
Blognoon: exploring a topic in the blogosphere
Authors: Maria P. Grineva, Maxim Grinev, Dmitry Lizorkin, Alexander Boldakov, Denis Turdakov, Andrey Syssoev, Alexander Kiyko
Venue: WWW
Year: 2011

We demonstrate Blognoon, a semantic blog search engine with the focus on topic exploration and navigation. Blognoon provides concept search instead of traditional keywords search and improves ranking by identifying main topics of posts. It enhances navigation over the Blogosphere with faceted interfaces and recommendations.
Visual query system for analyzing social semantic web
Authors: Jinghua Groppe, Sven Groppe, Andreas Schleifer
Venue: WWW
Year: 2011

The social web is becoming increasingly popular and important, because it creates the collective intelligence, which can produce more value than the sum of individuals. The social web uses the Semantic Web technology RDF to describe the social data in a machine-readable way. RDF query languages play certainly an important role in the social data analysis for extracting the collective intelligence. However, constructing such queries is not trivial since the social data is often quite large and assembled from a large number of different sources. In order to solve these challenges, we develop a Visual Query System (VQS) for helping the analysts of social data and other semantic data to formulate such queries easily and exactly. In this VQS, we suggest a condensed data view, a browser-like query creation system for absolute beginners and a Visual Query Language (VQL) for beginners and experienced users. Using the browser-like query creation or the VQL, the analysts of social data and other semantic data can construct queries with no or little syntax knowledge; using the condensed view, they can determine easily what queries should to be used. Furthermore, our system also supports precise suggestions to extend and refine existing queries.
The Lwazi community communication service: design and piloting of a voice-based information service
Authors: Aditi Sharma Grover, Etienne Barnard
Venue: WWW
Year: 2011

We present the design, development and pilot process of the Lwazi Community Communication Service (LCCS), a multilingual automated telephone-based information service. The service acts as a communication and dissemination tool that enables managers at local community centres to broadcast information (e.g. health, employment, social grants) to community workers and the communities they serve. The LCCS allows the recipients to obtain up-to-date, relevant information in a timely and efficient manner, overcoming the obstacles of transportation, time and costs incurred in trying to physically obtain information from the community centres. We discuss our experiences and fieldwork in piloting the LCCS at six locations nationally in the eleven official South African languages. We analyze the usage pattern from the pilot call logs and thereafter discuss the implications of these findings for future projects that design similar automated services for serving rural communities in developing world regions.
Embedding MindMap as a service for user-driven composition of web applications
Authors: Adnene Guabtni, Stuart Clarke, Boualem Benatallah
Venue: WWW
Year: 2011

The World Wide Web is evolving towards a very large distributed platform allowing ubiquitous access to a wide range of Web applications with minimal delay and no installation required. Such Web applications range from having users undertake simple tasks, such as filling a form, to more complex tasks including collaborative work, project management, and more generally, creating, consulting, annotating, and sharing Web content. However, users are lacking a simple but yet powerful mechanism to compose Web applications, similarly to what desktop environments allowed for decades using the file explorer paradigm and the desktop metaphor. Attempts have been made to adapt the desktop metaphor to the Web environment giving birth to Webtops (Web desktops). It essentially consisted of embedding a desktop environment in a Web browser and provide access to various Web applications within the same User Interface. However, those attempts did not take into consideration to the radical differences between Web and desktop environments and applications. In this work, we introduce a new approach for Web application composition based on the mindmap metaphor. It allows browsing artifacts (Web resources) and enabling user-driven composition of their associated Web applications. Essentially, a mindmap is a graph of widgets representing artifacts created or used by Web applications and allow to list and launch all possible Web applications associated to each artifact. A tool has been developed to experiment the new metaphor and is provided as a service to be embedded in Web applications via a Web browser's plug-in. We demonstrate in this paper three case studies regarding the DBLP Web site, Wikipedia and Google Picasa Web applications.
SmartInt: using mined attribute dependencies to integrate fragmented web databases
Authors: Ravi Gummadi, Anupam Khulbe, Aravind Kalavagattu, Sanil Salvi, Subbarao Kambhampati
Venue: WWW
Year: 2011

Many web databases can be seen as providing partial and overlapping information about entities in the world. To answer queries effectively, we need to integrate the information about the individual entities that are fragmented over multiple sources. At first blush this is just the inverse of traditional database normalization problem - rather than go from a universal relation to normalized tables, we want to reconstruct the universal relation given the tables (sources). The standard way of reconstructing the entities will involve joining the tables. Unfortunately, because of the autonomous and decentralized way in which the sources are populated, they often do not have Primary Key - Foreign Key relations. While tables do share attributes, direct joins over these shared attributes can result in reconstruction of many spurious entities thus seriously compromising precision. We present a unified approach that supports intelligent retrieval over fragmented web databases by mining and using inter-table dependencies. Experiments with the prototype implementation, SmartInt, show that its retrieval strikes a good balance between precision and recall.
Trust analysis with clustering
Authors: Manish Gupta, Yizhou Sun, Jiawei Han
Venue: WWW
Year: 2011

Web provides rich information about a variety of objects. Trustability is a major concern on the web. Truth establishment is an important task so as to provide the right information to the user from the most trustworthy source. Trustworthiness of information provider and the confidence of the facts it provides are inter-dependent on each other and hence can be expressed iteratively in terms of each other. However, a single information provider may not be the most trustworthy for all kinds of information. Every information provider has its own area of competence where it can perform better than others. We derive a model that can evaluate trustability on objects and information providers based on clusters (groups). We propose a method which groups the set of objects for which similar set of providers provide "good" facts, and provides better accuracy in addition to high quality object clusters.
Social recommender systems
Authors: Ido Guy, David Carmel
Venue: WWW
Year: 2011

The goal of this tutorial is to expose participants to the current research on social recommender systems (i.e., recommender systems for the social web). Participants will become familiar with state-of-the-art recommendation methods, their classifications according to various criteria, common evaluation methodologies, and potential applications that can utilize social recommender systems. Additionally, open issues and challenges in the field will be discussed.
Scalable integration and processing of linked data
Authors: Andreas Harth, Aidan Hogan, Spyros Kotoulas, Jacopo Urbani
Venue: WWW
Year: 2011

The goal of this tutorial is to introduce, motivate and detail techniques for integrating heterogeneous structured data from across the Web. Inspired by the growth in Linked Data publishing, our tutorial aims at educating Web researchers and practitioners about this new publishing paradigm. The tutorial will show how Linked Data enables uniform access, parsing and interpretation of data, and how this novel wealth of structured data can potentially be exploited for creating new applications or enhancing existing ones.
Helix: online enterprise data analytics
Authors: Oktie Hassanzadeh, Songyun Duan, Achille Fokoue, Anastasios Kementsietsidis, Kavitha Srinivas, Michael Jeffrey Ward
Venue: WWW
Year: 2011

The size, heterogeneity and dynamicity of data within an enterprise makes indexing, integration and analysis of the data increasingly difficult tasks. On the other hand, there has been a massive increase in the amount of high-quality open data available on the Web that could provide invaluable insights to data analysts and business intelligence specialists within the enterprise. The goal of Helix project is to provide users within the enterprise with a platform that allows them to perform online analysis of almost any type and amount of internal data using the power of external knowledge bases available on the Web. Such a platform requires a novel, data-format agnostic indexing mechanism, and light-weight data linking techniques that could link semantically related records across internal and external data sources of various characteristics. We present the initial architecture of our system and discuss several research challenges involved in building such a system.
Automatic sanitization of social network data to prevent inference attacks
Authors: Raymond Heatherly, Murat Kantarcioglu
Venue: WWW
Year: 2011

As the privacy concerns related to information release in social networks become a more mainstream concern, data owners will need to utilize a variety of privacy-preserving methods of examining this data. Here, we propose a method of data generalization that applies to social networks and present some initial findings for the utility/privacy tradeoff required for its use.
Pragmatic evaluation of folksonomies
Authors: Denis Helic, Markus Strohmaier, Christoph Trattner, Markus Muhr, Kristina Lerman
Venue: WWW
Year: 2011

Recently, a number of algorithms have been proposed to obtain hierarchical structures - so-called folksonomies - from social tagging data. Work on these algorithms is in part driven by a belief that folksonomies are useful for tasks such as: (a) Navigating social tagging systems and (b) Acquiring semantic relationships between tags. While the promises and pitfalls of the latter have been studied to some extent, we know very little about the extent to which folksonomies are pragmatically useful for navigating social tagging systems. This paper sets out to address this gap by presenting and applying a pragmatic framework for evaluating folksonomies. We model exploratory navigation of a tagging system as decentralized search on a network of tags. Evaluation is based on the fact that the performance of a decentralized search algorithm depends on the quality of the background knowledge used. The key idea of our approach is to use hierarchical structures learned by folksonomy algorithm as background knowledge for decentralized search. Utilizing decentralized search on tag networks in combination with different folksonomies as hierarchical background knowledge allows us to evaluate navigational tasks in social tagging systems. Our experiments with four state-of-the-art folksonomy algorithms on five different social tagging datasets reveal that existing folksonomy algorithms exhibit significant, previously undiscovered, differences with regard to their utility for navigation. Our results are relevant for engineers aiming to improve navigability of social tagging systems and for scientists aiming to evaluate different folksonomy algorithms from a pragmatic perspective.
Automatically generating labels based on unified click model
Authors: Guichun Hua, Min Zhang, Yiqun Liu, Shaoping Ma, Liyun Ru
Venue: WWW
Year: 2011

Ground truth labels are one of the most important parts in many test collections for information retrieval. Each label, depicting the relevance between a query-document pair, is usually judged by a human, and this process is timeconsuming and labor-intensive. Automatically Generating labels from click-through data has attracted increasing attention. In this paper, we propose a Unified Click Model to predict the multi-level labels, which aims at comprehensively considering the advantages of the Position Models and Cascade Models. Experiments show that the proposed click model outperforms the existing click models in predicting the multi-level labels, and could replace the labels judged by humans for test collections.
Allocating inverted index into flash memory for search engines
Authors: Bojun Huang, Zenglin Xia
Venue: WWW
Year: 2011

Although most large-scale web search engines adopt the standard DRAM-HDD storage hierarchy, the usage of hard disk is greatly limited by its long read latency. On the other hand, NAND Flash memory is 100x faster than hard disk and 10x cheaper than DRAM [2]. Therefore, it’s possible to allocate a significant portion of DRAM data into Flash memory, so as to save money on storage. This paper considers the optimal policy that allocates the DRAM portion of inverted index into Flash memory as much as possible. Note that the original hard disk portion of index data is still left in hard disk in our scheme, which actually results in a three-layer storage hierarchy. To our best knowledge, we are the first to show that it’s possible to get substantially better system performance for web index serving by trying some Flash-aware storage management approaches, rather than just plugging in a SSD and treating it as super hard disk. We limit our discussion in the static scenario, where posting lists are allocated atomically in either Flash memory or DRAM only when the index updates and no other data movement is performed at run time. The problem is very similar to static index caching/pruning [1] [4], except that the caching here is exclusive and the target storage is Flash memory. Note that previous work suggested that static policies work well for inverted index caching, compared with their dynamic counterparts [1].
Low-infrastructure methods to improve internet access for mobile users in emerging regions
Authors: Sibren Isaacman, Margaret Martonosi
Venue: WWW
Year: 2011

As information technology supports more aspects of modern life, digital access has become an important tool for developing regions to lift themselves from poverty. Though broadband internet connectivity will not be universally available in the short-term, widely-employed mobile devices coupled with novel delay-tolerant networking do allow limited forms of connectivity. This paper explores the design space for internet access systems operating with constrained connectivity. Our starting point is C-LINK, a collaborative caching system that enhances the performance of interactive web access over DTN and cellular connectivity. We discuss our experiences and results from deploying C-LINK in Nicaragua, before moving on to a broader design study of other issues that further influence operation. We consider the impact of (i) storing web content collaboratively cached across all user nodes, (ii) hybrid transport layers exploiting the best attributes of limited cellular and DTN-style connectivity. We also explore the behavior of future systems under a range of usage and mobility scenarios. Even under adverse conditions, our techniques can improve average service latency for page requests by a factor of 2X. Our results point to the considerable power of leveraging user mobility and collaboration in providing very-low-infrastructure internet access to developing regions.
First international workshop on social media engagement (SoME 2011)
Authors: Alejandro Jaimes, Mounia Lalmas, Yana Volkovich
Venue: WWW
Year: 2011

The goal of this workshop is to encourage discussion and sharing of ideas and research results on social media engagement. We aim to promote interdisciplinary research and exchange of ideas in this area, not only between industry and academia, but also between different fields (e.g., computer science, mathematics, physics, psychology, sociology, cultural anthropology, etc.). In particular, we would like to discuss approaches to address some of the serious research challenges we face in devising engagement metrics, in developing methodologies, and in understanding how different technical approaches can be used to enhance our understanding of user behavior in social media.
Domain-independent entity extraction from web search query logs
Authors: Alpa Jain, Marco Pennacchiotti
Venue: WWW
Year: 2011

Query logs of a Web search engine have been increasingly used as a vital source for data mining. This paper presents a study on large-scale domain-independent entity extraction from search query logs. We present a completely unsupervised method to extract entities by applying pattern-based heuristics and statistical measures. We compare against existing techniques that use Web documents as well as search logs, and show that we improve over the state of the art. We also provide an in-depth qualitative analysis outlining differences and commonalities between these methods.
Learning to re-rank: query-dependent image re-ranking using click data
Authors: Vidit Jain, Manik Varma
Venue: WWW
Year: 2011

Our objective is to improve the performance of keyword based image search engines by re-ranking their original results. To this end, we address three limitations of existing search engines in this paper. First, there is no straight-forward, fully automated way of going from textual queries to visual features. Image search engines therefore primarily rely on static and textual features for ranking. Visual features are mainly used for secondary tasks such as finding similar images. Second, image rankers are trained on query-image pairs labeled with relevance judgments determined by human experts. Such labels are well known to be noisy due to various factors including ambiguous queries, unknown user intent and subjectivity in human judgments. This leads to learning a sub-optimal ranker. Finally, a static ranker is typically built to handle disparate user queries. The ranker is therefore unable to adapt its parameters to suit the query at hand which again leads to sub-optimal results. We demonstrate that all of these problems can be mitigated by employing a re-ranking algorithm that leverages aggregate user click data.