OpenRaiser/Intern-Atlas huggingface dataset:
Instrumenting a logic programming language to gather provenance from an information extraction application
Authors: Christine F. Reilly, Yueh-Hsuan Chiang, Jeffrey F. Naughton
Venue: WWW
Year: 2012

Information extraction (IE) programs for the web consume and produce a lot of data. In order to better understand the program output, the developer and user often desire to know the details of how the output was created. Provenance can be used to learn about the creation of the output. We collect fine-grained provenance by leveraging ongoing work in the IE community to write IE programs in a logic programming language. The logic programming language exposes the semantics of the program, allowing us to gather fine-grained provenance during program execution. We discuss a case study using a web-based community information management system, then present results regarding the performance of queries over the provenance data gathered by our logic program interpreter. Our findings show that it is possible to gather useful fine-grained provenance during the execution of a logic based web information extraction program. Additionally, queries over this provenance information can be performed in a reasonable amount of time.
SAFE extensibility of data-driven web applications
Authors: Raphael M. Reischuk, Michael Backes, Johannes Gehrke
Venue: WWW
Year: 2012

This paper presents a novel method for enabling fast development and easy customization of interactive data-intensive web applications. Our approach is based on a high-level hierarchical programming model that results in both a very clean semantics of the application while at the same time creating well-defined interfaces for customization of application components. A prototypical implementation of a conference management system shows the efficacy of our approach.
Lexical quality as a proxy for web text understandability
Authors: Luz Rello, Ricardo Baeza-Yates
Venue: WWW
Year: 2012

We show that a recently introduced lexical quality measure is also valid to measure textual Web accessibility. Our measure estimates the lexical quality of a site based in the occurrence in English Web pages of a large set of words with errors. We first compute the correlation of our measure with Web popularity measures to show that gives independent information. Second, we carry out a user study using eye tracking to prove that the degree of lexical quality of a text is related to the degree of understandability of a text, one of the factors behind Web accessibility.
Finding expert users in community question answering
Authors: Fatemeh Riahi, Zainab Zolaktaf, M. Mahdi Shafiei, Evangelos E. Milios
Venue: WWW
Year: 2012

Community Question Answering (CQA) websites provide a rapidly growing source of information in many areas. This rapid growth, while offering new opportunities, puts forward new challenges. In most CQA implementations there is little effort in directing new questions to the right group of experts. This means that experts are not provided with questions matching their expertise, and therefore new matching questions may be missed and not receive a proper answer. We focus on finding experts for a newly posted question. We investigate the suitability of two statistical topic models for solving this issue and compare these methods against more traditional Information Retrieval approaches. We show that for a dataset constructed from the Stackoverflow website, these topic models outperform other methods in retrieving a candidate set of best experts for a question. We also show that the Segmented Topic Model gives consistently better performance compared to the Latent Dirichlet Allocation Model.
Email between private use and organizational purpose
Authors: Uwe V. Riss
Venue: WWW
Year: 2012

Emails have become an eminent source of personal and organizational information. They are not only used for personal communication but also for the management of information and the coordination of activities within organizations. Email traffic also exhibits the social networks existing in organizations. However, the central problem, which we still face, is how to tap this rich source appropriately. Main problems in this respect are the personal character of emails (their privacy) and the mainly unstructured character of their contents. Since these two features are essential success factors for the use of email they cannot be simply ignored. Meanwhile there are various approaches to recover the hidden treasure and make the contained information available to information and process management. For example, semantic or mining technologies play a prominent role in this attempt. The paper gives an overview of different strategies to make organizational use of emails, also touching the role of privacy.
ARCOMEM: from collect-all ARchives to COmmunity MEMories
Authors: Thomas Risse, Wim Peters
Venue: WWW
Year: 2012

The ARCOMEM project is about memory institutions like archives, museums and libraries in the age of the Social Web. Social media are becoming more and more pervasive in all areas of life. ARCOMEM's aim is to help to transform archives into collective memories that are more tightly integrated with their community of users and to exploit Web 2.0 and the wisdom of crowds to make Web archiving a more selective and meaning-based process. ARCOMEM (FP7-IST-270239) is an Integrating Project in the FP7 program of the European Commission, which involves twelve partners from academia, industry and public sector. The project will run from January 1, 2011 to December 31, 2013.
From network mining to large scale business networks
Authors: Daniel Ritter
Venue: WWW
Year: 2012

The vision of Large Scale Network Analysis (LSNA) states on large amounts of network data, which are produced by social media applications like Facebook, Twitter, and the competitive domain of biological networks as well as their needs for network data extraction and analysis. That raises data management challenges which are addressed by biological, data mining and linked (web) data management communities. So far, mainly these domains were considered when identifying research topics and measuring approaches and progress. We argue that an important domain, the Business Network Management (BNM), representing business and (technical) integration data, implicitely linked and available in enterprises, has been neglected. Not only do enterprises need visibilities into their business networks, they need ad-hoc analysis capabilities on them. In this paper, we introduce BNM as domain, which comes with large scale network data. We discuss how linked business data can be made explicit by what we called Network Mining (NM) from dynamic, heterogeneous enterprise environments to combine it to a (cross-) enterprise linked business data network and state on its different facets w.r.t large network analysis and highlight challenges and opportunities.
S2S architecture and faceted browsing applications
Authors: Eric Rozell, Peter Fox, Jinguang Zheng, Jim Hendler
Venue: WWW
Year: 2012

This demo paper will discuss a search interface framework designed as part of the Semantic eScience Framework project at the Tetherless World Constellation. The search interface framework, S2S, was designed to facilitate the construction of interactive user interfaces for data catalogs. We use Semantic Web technologies, including an OWL ontology for describing the semantics of data services, as well as the semantics of user interface components. We have applied S2S in three different scenarios: (1) the development of a faceted browse interface integrated with an interactive mapping and visualization tool for biological and chemical oceanographic data, (2) the development of a faceted browser for more than 700,000 open government datasets in over 100 catalogs worldwide, and (3) the development of a user interface for a virtual observatory in the field of solar-terrestrial physics. Throughout this paper, we discuss the architecture of the S2S framework, focusing on its extensibility and reusability, and also review the application scenarios.
Context-aware image semantic extraction in the social web
Authors: Massimiliano Ruocco
Venue: WWW
Year: 2012

Media sharing applications such as Panoramio and Flickr contain a huge amount of pictures that need to be organized to facilitate browsing and retrieval. Such pictures are often surrounded by a set of metadata or image tags, constituting the image context. With the advent of the paradigm of Web 2.0 especially the past five years, the concept of image context has further evolved, allowing users to tag their own and other people's pictures. Focusing on tagging, we distinguish between static and dynamic features. The set of static features include textual and visual features, as well as the contextual information. Further, we may identify other features belonging to the social context as a result of the usage within the media sharing applications. Due to their dynamic nature, we call these the dynamic set of features. In this work, we assume that every media uploaded contains both static and dynamic features. In addition, a user may be linked with other users with whom he/she shares common interests. This has resulted in a new series of challenges within the research field of semantic understanding. One of the main goals of this work is to address these challenges.
Socio-semantic conversational information access
Authors: Saurav Sahay, Ashwin Ram
Venue: WWW
Year: 2012

The main contributions of this thesis revolve around development of an integrated conversational recommendation system, combining data and information models with community network and interactions to leverage multi-modal information access. We have developed a real time conversational information access community agent that leverages community knowledge by pushing relevant recommendations to users of the community. The recommendations are delivered in the form of web resources, past conversation and people to connect to. The information agent (cobot, for community/ collaborative bot) monitors the community conversations, and is 'aware' of users' preferences by implicitly capturing their short term and long term knowledge models from conversations. The agent leverages from health and medical domain knowledge to extract concepts, associations and relationships between concepts; formulates queries for semantic search and provides socio-semantic recommendations in the conversation after applying various relevance filters to the candidate results. The agent also takes into account users' verbal intentions in conversations while making recommendation decision.\n\nOne of the goals of this thesis is to develop an innovative approach to delivering relevant information using a combination of social networking, information aggregation, semantic search and recommendation techniques. The idea is to facilitate timely and relevant social information access by mixing past community specific conversational knowledge and web information access to recommend and connect users with relevant information. \n\n\nLanguage and interaction creates usable memories, useful for making decisions about what actions to take and what information to retain. Cobot leverages these interactions to maintain users' episodic and long term semantic models. The agent\nanalyzes these memory structures to match and recommend users in conversations by matching with the contextual information need. The social feedback on the recommendations is registered in the system for the algorithms to promote community\npreferred, contextually relevant resources.\nThe nodes of the semantic memory are frequent concepts extracted from user's interactions. The concepts are connected with associations that develop when concepts co-occur frequently. Over a period of time when the user participates in more interactions, new concepts are added to the semantic memory. Different conversational\nfacets are matched with episodic memories and a spreading activation search on the\nsemantic net is performed for generating the top candidate user recommendations for the conversation. \n\nThe tying themes in this thesis revolve around informational and social aspects of a unified information access architecture that integrates semantic extraction and indexing with user modeling and recommendations.
Graph embedding on spheres and its application to visualization of information diffusion data
Authors: Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda
Venue: WWW
Year: 2012

We address the problem of visualizing structure of undirected graphs that have a value associated with each node into a K-dimensional Euclidean space in such a way that 1) the length of the point vector in this space is equal to the value assigned to the node and 2) nodes that are connected are placed as close as possible to each other in the space and nodes not connected are placed as far apart as possible from each other. The problem is reduced to K-dimensional spherical embedding with a proper objective function. The existing spherical embedding method can handle only a bipartite graph and cannot be used for this purpose. The other graph embedding methods, e.g., multi-dimensional scaling, spring force embedding methods, etc., cannot handle the value constraint and thus are not applicable, either. We propose a very efficient algorithm based on a power iteration that employs the double-centering operations. We apply the method to visualize the information diffusion process over a social network by assigning the node activation time to the node value, and compare the results with the other visualization methods. The results applied to four real world networks indicate that the proposed method can visualize the diffusion dynamics which the other methods cannot and the role of important nodes, e.g. mediator, more naturally than the other methods.
Plan4All GeoPortal: web of spatial data
Authors: Evangelos Sakkopoulos, Tomas Mildorf, Karel Charvát, Inga Berzina, Kai-Uwe Krause
Venue: WWW
Year: 2012

Plan4All project contributes on the harmonization of spatial data and related metadata in order to make them available through Web across a linked data platform. A prototype of a Web search European spatial data portal is already available at http://www.plan4all.eu. The key aim is to provide a methodology and present best practices towards the standardization of spatial data according to the INSPIRE principles and provide results that would be a reference material for linking data and data specification from the spatial planning point of view. The results include methodology and implementation of multilingual search for data and common portrayal rules for content providers. These are critical services for sharing and understanding spatial data across Europe. Plan4All paradigm shows that a clear applicable methodology for harmonization of spatial data on all different topics of interest can be achieve efficiently. Plan4All shows that it is possible to build Pan European Web access, to link spatial data and to utilize multilingual metadata providing a roadmap for linked spatial data across and hopefully beyond Europe. The proposed demonstration based on Plan4All experience aims to show experience, best practices and methods to achieve data harmonization and provision of linked spatial data on the Web.
Mass and social media corpus analysis after the 2011 great east Japan earthquake
Authors: Shosuke Sato, Michiaki Tatsubori, Fumihiko Imamura
Venue: WWW
Year: 2012

In this paper, we outline our analysis of mass media and social media as used for disaster management. We looked at the differences among multiple sub-corpuses to find relatively unique keywords based on chronologies, geographic locations, or media types. We are currently analyzing a massive corpus collected from Internet news sources and Twitter after the Great East Japan Earthquake.
Mining microblogs to infer music artist similarity and cultural listening patterns
Authors: Markus Schedl, David Hauger
Venue: WWW
Year: 2012

This paper aims at leveraging microblogs to address two challenges in music information retrieval (MIR), similarity estimation between music artists and inferring typical listening patterns at different granularity levels (city, country, global). From two collections of several million microblogs, which we gathered over ten months, music-related information is extracted and statistically analyzed. We propose and evaluate four co-occurrence-based methods to compute artist similarity scores. Moreover, we derive and analyze culture-specific music listening patterns to investigate the diversity of listening behavior around the world.
Community cores in evolving networks
Authors: Massoud Seifi, Jean-Loup Guillaume
Venue: WWW
Year: 2012

Community structure is a key property of complex networks. Many algorithms have been proposed to automatically detect communities in static networks but few studies have considered the detection and tracking of communities in an evolving network. Tracking the evolution of a given community over time requires a clustering algorithm that produces stable clusters. However, most community detection algorithms are very unstable and therefore unusable for evolving networks. In this paper, we apply the methodology proposed in [seifi2012] to detect what we call community cores in evolving networks. We show that cores are much more stable than "classical" communities and that we can overcome the disadvantages of the stabilized methods.
Latent contextual indexing of annotated documents
Authors: Christian Sengstock, Michael Gertz
Venue: WWW
Year: 2012

In this paper we propose a simple and flexible framework to index context-annotated documents, e.g., documents with timestamps or georeferences, by contextual topics. A contextual topic is a distribution over document features with a particular meaning in the context domain, such as a repetitive event or a geographic phenomenon. Such a framework supports document clustering, labeling, and search, with respect to contextual knowledge contained in the document collection. To realize the framework, we introduce an approach to project documents into a context-feature space. Then, dimensionality reduction is used to extract contextual topics in this context-feature space. The topics can then be projected back onto the documents. We demonstrate the utility of our approach with a case study on georeferenced Wikipedia articles.
Data gathering for a culture specific approach in MIR
Authors: Xavier Serra
Venue: WWW
Year: 2012

In this paper we describe the data gathering work done within a large research project, CompMusic, which emphasizes a culture specific approach in the automatic description of several world music repertoires. Currently we are focusing on the Hindustani (North India), Carnatic (South India) and Turkish-makam (Turkey) music traditions. The selection and organization of the data to be processed for the characterization of each of these traditions is of the utmost importance.
APOLLO: a general framework for populating ontology with named entities via random walks on graphs
Authors: Wei Shen, Jianyong Wang, Ping Luo, Min Wang
Venue: WWW
Year: 2012

Automatically populating ontology with named entities extracted from the unstructured text has become a key issue for Semantic Web. This issue naturally consists of two subtasks: (1) for the entity mention whose mapping entity does not exist in the ontology, attach it to the right category in the ontology (i.e., fine-grained named entity classification), and (2) for the entity mention whose mapping entity is contained in the ontology, link it with its mapping real world entity in the ontology (i.e., entity linking). Previous studies only focus on one of the two subtasks. This paper proposes APOLLO, a general weakly supervised frAmework for POpuLating ontoLOgy with named entities. APOLLO leverages the rich semantic knowledge embedded in the Wikipedia to resolve this task via random walks on graphs. An experimental study has been conducted to show the effectiveness of APOLLO.
Entity based translation language model
Authors: Amit Singh
Venue: WWW
Year: 2012

Bridging the lexical gap between the user's question and the question-answer pairs in Q&A archives has been a major challenge for Q&A retrieval. State-of-the-art approaches address this issue by implicitly expanding the queries with additional words using statistical translation models. In this work we extend the lexical word based translation model to incorporate semantic concepts. We explore strategies to learn the translation probabilities between words and the concepts using the Q&A archives and Wikipedia. Experiments conducted on a large scale real data from Yahoo Answers! show that the proposed techniques are promising and need further investigation.
Rewriting null e-commerce queries to recommend products
Authors: Gyanit Singh, Nish Parikh, Neel Sundaresan
Venue: WWW
Year: 2012

In e-commerce applications product descriptions are often concise. E-Commerce search engines often have to deal with queries that cannot be easily matched to product inventory resulting in zero recall or null query situations. Null queries arise from differences in buyer and seller vocabulary or from the transient nature of products. In this paper, we describe a system that rewrites null e-commerce queries to find matching products as close to the original query as possible. The system uses query relaxation to rewrite null queries in order to match products. Using eBay as an example of a dynamic marketplace, we show how using temporal feedback that respects product category structure using the repository of expired products, we improve the quality of recommended results. The system is scalable and can be run in a high volume setting. We show through our experiments that high quality product recommendations for more than 25% of null queries are achievable.
Rumor spreading and inoculation of nodes in complex networks
Authors: Anurag Singh, Yatindra Nath Singh
Venue: WWW
Year: 2012

Over the Internet or on social networks rumors can spread and can affect the society in disaster. The question one asks about this phenomenon is that whether these rumors can be suppressed using suitable mechanisms. One of the possible solutions is to inoculate a certain fraction of nodes against rumors. The inoculation can be done randomly or in targeted fashion. In this paper, small world network model has been used to investigate the efficiency of inoculation. It has been found that if average degree of small world network is small than both inoculation methods are successful. When average degree is large, neither of these methods are able to stop rumor spreading. But if acceptability of rumor is reduced along with inoculation, the rumor spreading can be stopped even in this case.The proposed hypothesis has been verified using simulation experiments.
Practical end-to-end web content integrity
Authors: Kapil Singh, Helen J. Wang, Alexander Moshchuk, Collin Jackson, Wenke Lee
Venue: WWW
Year: 2012

Widespread growth of open wireless hotspots has made it easy to carry out man-in-the-middle attacks and impersonate web sites. Although HTTPS can be used to prevent such attacks, its universal adoption is hindered by its performance cost and its inability to leverage caching at intermediate servers (such as CDN servers and caching proxies) while maintaining end-to-end security. To complement HTTPS, we revive an old idea from SHTTP, a protocol that offers end-to-end web integrity without confidentiality. We name the protocol HTTPi and give it an efficient design that is easy to deploy for today's web. In particular, we tackle several previously-unidentified challenges, such as supporting progressive page loading on the client's browser, handling mixed content, and defining access control policies among HTTP, HTTPi, and HTTPS content from the same domain. Our prototyping and evaluation experience show that HTTPi incurs negligible performance overhead over HTTP, can leverage existing web infrastructure such as CDNs or caching proxies without any modifications to them, and can make many of the mixed-content problems in existing HTTPS web sites easily go away. Based on this experience, we advocate browser and web server vendors to adopt HTTPi.