OpenRaiser/Intern-Atlas huggingface dataset:
The patents retrieval prototype in the MOLTO project
Authors: Milen Chechev, Meritxell González, Lluís Màrquez, Cristina España-Bonet
Venue: WWW
Year: 2012

This paper describes the patents retrieval prototype developed within the MOLTO project. The prototype aims to provide a multilingual natural language interface for querying the content of patent documents. The developed system is focused on the biomedical and pharmaceutical domain and includes the translation of the patent claims and abstracts into English, French and German. Aiming at the best retrieval results of the patent information and text content, patent documents are preprocessed and semantically annotated. Then, the annotations are stored and indexed in an OWLIM semantic repository, which contains a patent specific ontology and others from different domains. The prototype, accessible online at http://molto-patents.ontotext.com, presents a multilingual natural language interface to query the retrieval system. In MOLTO, the multilingualism of the queries is addressed by means of the GF Tool, which provides an easy way to build and maintain controlled language grammars for interlingual translation in limited domains. The abstract representation obtained from the GF is used to retrieve both the matched RDF instances and the list of patents semantically related to the user's search criteria. The online interface allows to browse the retrieved patents and shows on the text the semantic annotations that explain the reason why any particular patent has matched the user's criteria.
Privacy management for online social networks
Authors: Gorrell P. Cheek, Mohamed Shehab
Venue: WWW
Year: 2012

We introduce a privacy management approach that leverages users' memory and opinion of their friends to set policies for other similar friends. We refer to this new approach as Same-As Privacy Management. To demonstrate the effectiveness of our privacy management improvements, we implemented a prototype Facebook application and conducted an extensive user study. We demonstrated considerable reductions in policy authoring time using Same-As Privacy Management over traditional group based privacy management approaches. Finally, we presented user perceptions, which were very encouraging.
Fast and cost-efficient bid estimation for contextual ads
Authors: Ye Chen, Pavel Berkhin, Jie Li, Sharon Wan, Tak W. Yan
Venue: WWW
Year: 2012

We study the problem of estimating the value of a contextual ad impression, and based upon which an ad network bids on an exchange. The ad impression opportunity would materialize into revenue only if the ad network wins the impression and a user clicks on the ads, both as a rare event especially in an open exchange for contextual ads. Given a low revenue expectation and the elusive nature of predicting weak-signal click-through rates, the computational cost incurred by bid estimation shall be cautiously justified. We developed and deployed a novel impression valuation model, which is expected to reduce the computational cost by 95% and hence more than double the profit. Our approach is highly economized through a fast implementation of kNN regression that primarily leverages low-dimensional sell-side data (user and publisher). We also address the cold-start problem or the exploration vs. exploitation requirement by Bayesian smoothing using a beta prior, and adapt to the temporal dynamics using an autoregressive model.
Fast query evaluation for ad retrieval
Authors: Ye Chen, Mitali Gupta, Tak W. Yan
Venue: WWW
Year: 2012

We describe a fast query evaluation method for ad document retrieval in online advertising, based upon the classic WAND algorithm. The key idea is to localize per-topic term upper bounds into homogeneous ad groups. Our approach is not only theoretically motivated by a topical mixture model; but empirically justified by the characteristics of the ad domain, that is, short and semantically focused documents with natural hierarchy. We report experimental results using artificial and real-world query-ad retrieval data, and show that the tighter-bound WAND outperforms the traditional approach by 35.4% reduction in number of full evaluations.
Understanding web images by object relation network
Authors: Na Chen, Qian-Yi Zhou, Viktor K. Prasanna
Venue: WWW
Year: 2012

This paper presents an automatic method for understanding and interpreting the semantics of unannotated web images. We observe that the relations between objects in an image carry important semantics about the image. To capture and describe such semantics, we propose Object Relation Network (ORN), a graph model representing the most probable meaning of the objects and their relations in an image. Guided and constrained by an ontology, ORN transfers the rich semantics in the ontology to image objects and the relations between them, while maintaining semantic consistency (e.g., a soccer player can kick a soccer ball, but cannot ride it). We present an automatic system which takes a raw image as input and creates an ORN based on image visual appearance and the guide ontology. We demonstrate various useful web applications enabled by ORNs, such as automatic image tagging, automatic image description generation, and image search by image.
Is this app safe?: a large scale study on application permissions and risk signals
Authors: Pern Hui Chia, Yusuke Yamamoto, N. Asokan
Venue: WWW
Year: 2012

Third-party applications (apps) drive the attractiveness of web and mobile application platforms. Many of these platforms adopt a decentralized control strategy, relying on explicit user consent for granting permissions that the apps request. Users have to rely primarily on community ratings as the signals to identify the potentially harmful and inappropriate apps even though community ratings typically reflect opinions about perceived functionality or performance rather than about risks. With the arrival of HTML5 web apps, such user-consent permission systems will become more widespread. We study the effectiveness of user-consent permission systems through a large scale data collection of Facebook apps, Chrome extensions and Android apps. Our analysis confirms that the current forms of community ratings used in app markets today are not reliable indicators of privacy risks of an app. We find some evidence indicating attempts to mislead or entice users into granting permissions: free applications and applications with mature content request more permissions than is typical; 'look-alike' applications which have names similar to popular applications also request more permissions than is typical. We also find that across all three platforms popular applications request more permissions than average.
CONSENTO: a consensus search engine for answering subjective queries
Authors: Jaehoon Choi, Donghyeon Kim, Seongsoon Kim, Junkyu Lee, Sangrak Lim, Sunwon Lee, Jaewoo Kang
Venue: WWW
Year: 2012

Search engines have become an important decision making tool today. Decision making queries are often subjective, such as 'best sedan for family use,' 'best action movies in 2010,' to name a few. Unfortunately, such queries cannot be answered properly by conventional search systems. In order to address this problem, we introduce Consento, a consensus search engine designed to answer subjective queries. Consento performs subdocument-level indexing to more precisely capture semantics from user opinions. We also introduce a new ranking method, or ConsensusRank that counts in online comments referring to an entity as a weighted vote to the entity. We validated the framework with an empirical study using the data on movie reviews.
Good abandonments in factoid queries
Authors: Aleksandr Chuklin, Pavel Serdyukov
Venue: WWW
Year: 2012

It is often considered that high abandonment rate corresponds to poor IR system performance. However several studies suggested that there are so called good abandonments, i.e. situations when search engine result page (SERP) contains enough details to satisfy the user information need without necessity to click on search results. In those papers only editorial metrics of SERP were used, and one cannot be sure that situations marked as good abandonments by assessors actually imply user satisfaction. In present work we propose some real-world evidences for good abandonments by calculating correlation between editorial and click metrics.
Potential good abandonment prediction
Authors: Aleksandr Chuklin, Pavel Serdyukov
Venue: WWW
Year: 2012

Abandonment rate is one of the most broadly used online user satisfaction metrics. In this paper we discuss the notion of potential good abandonment, i.e. queries that may potentially result in user satisfaction without the need to click on search results (if search engine result page contains enough details to satisfy the user information need). We show, that we can train a classifier which is able to distinguish between potential good and bad abandonments with rather good results compared to our baseline. As a case study we show how to apply these ideas to IR evaluation and introduce a new metric for A/B-testing -- Bad Abandonment Rate.
Your two weeks of fame and your grandmother's
Authors: James Cook, Atish Das Sarma, Alex Fabrikant, Andrew Tomkins
Venue: WWW
Year: 2012

Did celebrity last longer in 1929, 1992 or 2009? We investigate the phenomenon of fame by mining a collection of news articles that spans the twentieth century, and also perform a side study on a collection of blog posts from the last 10 years. By analyzing mentions of personal names, we measure each person's time in the spotlight, and watch the distribution change from a century ago to a year ago. We expected to find a trend of decreasing durations of fame as news cycles accelerated and attention spans became shorter. Instead, we find a remarkable consistency through most of the period we study. Through a century of rapid technological and societal change, through the appearance of Twitter, communication satellites and the Internet, we do not observe a significant change in typical duration of celebrity. We also study the most famous of the famous, and find different results depending on our method for measuring duration of fame. With a method that may be thought of as measuring a spike of attention around a single narrow news story, we see the same result as before: stories last as long now as they did in 1930. A second method, which may be thought of as measuring the duration of public interest in a person, indicates that famous people's presence in the news is becoming longer rather than shorter, an effect most likely driven by the wider distribution and higher volume of media in modern times. Similar studies have been done with much shorter timescales specifically in the context of information spreading on Twitter and similar social networking site. However, to the best of our knowledge, this is the first massive scale study of this nature that spans over a century of archived data, thereby allowing us to track changes across decades.
A fast algorithm to find all high degree vertices in power law graphs
Authors: Colin Cooper, Tomasz Radzik, Yiannis Siantos
Venue: WWW
Year: 2012

Sampling from large graphs is an area which is of great interest, particularly with the recent emergence of huge structures such as Online Social Networks. These often contain hundreds of millions of vertices and billions of edges. The large size of these networks makes it computationally expensive to obtain structural properties of the underlying graph by exhaustive search. If we can estimate these properties by taking small but representative samples from the network, then size is no longer a problem.
Ubiquitous access control for SPARQL endpoints: lessons learned and future challenges
Authors: Luca Costabello, Serena Villata, Nicolas Delaforge, Fabien Gandon
Venue: WWW
Year: 2012

We present and evaluate a context-aware access control framework for SPARQL endpoints queried from mobile.
Strategic formation of credit networks
Authors: Pranav Dandekar, Ashish Goel, Michael P. Wellman, Bryce Wiedenbeck
Venue: WWW
Year: 2012

Credit networks are an abstraction for modeling trust between agents in a network. Agents who do not directly trust each other can transact through exchange of IOUs (obligations) along a chain of trust in the network. Credit networks are robust to intrusion, can enable transactions between strangers in exchange economies, and have the liquidity to support a high rate of transactions. We study the formation of such networks when agents strategically decide how much credit to extend each other. When each agent trusts a fixed set of other agents, and transacts directly only with those it trusts, the formation game is a potential game and all Nash equilibria are social optima. Moreover, the Nash equilibria of this game are equivalent in a very strong sense: the sequences of transactions that can be supported from each equilibrium credit network are identical. When we allow transactions over longer paths, the game may not admit a Nash equilibrium, and even when it does, the price of anarchy may be unbounded. Hence, we study two special cases. First, when agents have a shared belief about the trustworthiness of each agent, the networks formed in equilibrium have a star-like structure. Though the price of anarchy is unbounded, myopic best response quickly converges to a social optimum. Similar star-like structures are found in equilibria of heuristic strategies found via simulation. In addition, we simulate a second case where agents may have varying information about each others' trustworthiness based on their distance in a social network. Empirical game analysis of these scenarios suggests that star structures arise only when defaults are relatively rare, and otherwise, credit tends to be issued over short social distances conforming to the locality of information.
Multilingual online generation from semantic web ontologies
Authors: Dana Dannélls, Mariana Damova, Ramona Enache, Milen Chechev
Venue: WWW
Year: 2012

In this paper we report on our ongoing work in the EU project Multilingual Online Translation (MOLTO), supported by the European Union Seventh Framework Programme under grant agreement FP7-ICT-247914. More specifically, we present work workpackage 8 (WP8): Case Study: Cultural Heritage. The objective of the work is to build an ontology-based multilingual application for museum information on the Web. Our approach relies on the innovative idea of Reason-able View of the Web of linked data applied to the domain of cultural heritage. We have been developing a Web application that uses Semantic Web ontologies for generating coherent multilingual natural language descriptions about museum objects. We have been experimenting with museum data to test our approach and find that it performs well for the examined languages.
FreeQ: an interactive query interface for freebase
Authors: Elena Demidova, Xuan Zhou, Wolfgang Nejdl
Venue: WWW
Year: 2012

Freebase is a large-scale open-world database where users collaboratively create and structure content over an open platform. Keyword queries over Freebase are notoriously ambiguous due to the size and the complexity of the dataset. To this end, novel techniques are required to enable naive users to express their informational needs and retrieve the desired data. FreeQ offers users an interactive interface for incremental query construction over a large-scale dataset, so that the users can find desired information quickly and accurately.
Making use of social media data in public health
Authors: Kerstin Denecke, Peter Dolog, Pavel Smrz
Venue: WWW
Year: 2012

Disease surveillance systems exist to offer an easily accessible "epidemiological snapshot" on up-to-date summary statistics for numerous infectious diseases. However, these indicator-based systems represent only part of the solution. Experiences show that they fail when confronted with agents that are new emerging like the agents causing the lung disease SARS in 2002. Further, due to slow reporting mechanisms, the time until health threats become visible to public health officials can be long. The M-Eco project provides an event-based approach to the early detection of emerging health threats. The developed technologies exploit content from social media and multimedia data as input and analyze it by sophisticated event-detection techniques to identify potential threats. Alerts for public health threats are provided to the user in a personalized way.
Declarative platform for data sourcing games
Authors: Daniel Deutch, Ohad Greenshpan, Boris Kostenko, Tova Milo
Venue: WWW
Year: 2012

Harnessing a crowd of users for the collection of mass data (data sourcing) has recently become a wide-spread practice. One effective technique is based on games as a tool that attracts the crowd to contribute useful facts. We focus here on the data management layer of such games, and observe that the development of this layer involves challenges such as dealing with probabilistic data, combined with recursive manipulation of this data. These challenges are difficult to address using current declarative data management framework works, and we thus propose here a novel such framework, and demonstrate its usefulness in expressing different aspects in the data management of Trivia-like games. We have implemented a system prototype with our novel data management framework at its core, and we highlight key issues in the system design, as well as our experimentations that indicate the usefulness and scalability of the approach.
Towards personalized learning to rank for epidemic intelligence based on social media streams
Authors: Ernesto Diaz-Aviles, Avaré Stewart, Edward Velasco, Kerstin Denecke, Wolfgang Nejdl
Venue: WWW
Year: 2012

In the presence of sudden outbreaks, how can social media streams be used to strengthen surveillance capabilities? In May 2011, Germany reported one of the largest described outbreaks of Enterohemorrhagic Escherichia coli (EHEC). By end of June, 47 persons had died. After the detection of the outbreak, authorities investigating the cause and the impact in the population were interested in the analysis of micro-blog data related to the event. Since Thousands of tweets related to this outbreak were produced every day, this task was overwhelming for experts participating in the investigation. In this work, we propose a Personalized Tweet Ranking algorithm for Epidemic Intelligence (PTR4EI), that provides users a personalized, short list of tweets based on the user's context. PTR4EI is based on a learning to rank framework and exploits as features, complementary context information extracted from the social hash-tagging behavior in Twitter. Our experimental evaluation on a dataset, collected in real-time during the EHEC outbreak, shows the superior ranking performance of PTR4EI. We believe our work can serve as a building block for an open early warning system based on Twitter, helping to realize the vision of Epidemic Intelligence for the Crowd, by the Crowd.
"Making sense of it all": an attempt to aid journalists in analysing and filtering user generated content
Authors: Sotiris Diplaris, Symeon Papadopoulos, Ioannis Kompatsiaris, Nicolaus Heise, Jochen Spangenberg, Nic Newman, Hakim Hacid
Venue: WWW
Year: 2012

This position paper explores how journalists can embrace new ways of content provision and authoring, by aggregating and analyzing content gathered from Social Media. Current challenges in the news media industry are reviewed and a new system for capturing emerging knowledge from Social Media is described. Novel features that assist professional journalists in processing sheer amounts of Social Media information are presented with a reference to the technical requirements of the system. First implementation steps are also discussed, particularly focusing in event detection and user influence identification.
Musubi: disintermediated interactive social feeds for mobile devices
Authors: Ben Dodson, Ian Vo, T. J. Purtell, Aemon Cannon, Monica S. Lam
Venue: WWW
Year: 2012

This paper presents Musubi, a mobile social application platform that enables users to share any data type in real-time feeds created by any application on the phone. Musubi is unique in providing a disintermediated service to end users; all communication is supported using public key encryption thus leaking no user information to a third party. Despite the heavy use of cryptography to provide user authentication and access control, users found Musubi simple to use. We embed key exchange within familiar friending actions, and allow users to interact with any friend in their address books without requiring them to join a common network a priori. Our feed abstraction allows users to easily exercise access control. All data reside on the phone, granting users the freedom to apply applications of their choice.
Querying socio-spatial networks on the world-wide web
Authors: Yerach Doytsher, Ben Galon, Yaron Kanza
Venue: WWW
Year: 2012

navigation systems, allow users to record their location history. The location history data can be analyzed to generate life patterns|patterns that associate people to places they frequently visit. Accordingly, an SSN is a graph that consists of (1) a social network, (2) a spatial network, and (3) life patterns that connect the users of the social network to locations, i.e., to geographical entities in the spatial network. In this paper we present a system that stores SNN in a graph-based database management system and provides a novel query language, namely SSNQL, for querying the integrated data. The system includes a Web-based graphical user interface that allows presenting the social network, presenting the spatial network and posing SSNQL queries over the integrated data. The user interface also depicts the structure of queries for the purpose of debugging and optimization. Our demonstration presents the management of the integrated data as an SSN and it illustrates the query evaluation process in SSNQL.
Social media and SMS in the haiti earthquake
Authors: Julie Dugdale, Bartel A. Van de Walle, Corinna Koeppinghoff
Venue: WWW
Year: 2012

We describe some first results of an empirical study describing how social media and SMS were used in coordinating humanitarian relief after the Haiti Earthquake in January 2010. Current information systems for crisis management are increasingly incorporating information obtained from citizens transmitted via social media and SMS. This information proves particularly useful at the aggregate level. However it has led to some problems: information overload and processing difficulties, variable speed of information delivery, managing volunteer communities, and the high risk of receiving inaccurate or incorrect information.
D2RQ/update: updating relational data via virtual RDF
Authors: Vadim Eisenberg, Yaron Kanza
Venue: WWW
Year: 2012

D2RQ is a popular RDB-to-RDF mapping platform that supports mapping relational databases to RDF and posing SPARQL queries to these relational databases. However, D2RQ merely provides a read-only RDF view on relational databases. Thus, we introduce D2RQ/Update---an extension of D2RQ to enable executing SPARQL/Update statements on the mapped data, and to facilitate the creation of a read-write Semantic Web.