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SWJ 2011 : Semantic Web Journal special issue on The Personal and Social Semantic Web | |||||||||||||||
Link: http://wis.ewi.tudelft.nl/swj2011/ | |||||||||||||||
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Call For Papers | |||||||||||||||
Call for Papers
Semantic Web Journal Special Issue on The Personal and Social Semantic Web Website: http://wis.ewi.tudelft.nl/swj2011/ SWJ: http://www.semantic-web-journal.net/ About ======== Social Web sites, such as Facebook, YouTube, Delicious, Flickr and Wikipedia, and numerous other Web applications, such as Google and Amazon, rely on implicitly or explicitly collected data about their users and their activities to provide personalized content and services. As these applications become more and more connected on the Semantic Web, a major challenge is to allow various applications to exchange, reuse, and integrate user data from different sources. Such data comes in different flavors: user data such as user profiles, social networking/tagging/blogging data, etc. as well as usage data like clickthrough data or query logs. The amount of people's data available on the Web is tremendously growing so that sharing and mining these heterogeneous data corpora distributed on the Web is a non-trivial problem that poses several challenges to the Semantic Web community. Semantic interoperability between Social Web applications is becoming increasingly important as users leave a plethora of traces at diverse services on the Web. Semantic Web and Social Web technologies and paradigms provide means to facilitate integration of user and usage data, for example, with the principles of Linked Data and Microformats, vocabulary standards such as FOAF and SIOC, standardized APIs such as OpenSocial, or support for schema matching as provided by the Silk framework. Further, mechanisms like WebID, OpenId, OAuth and FOAF+SSL allow for identification and authorization on the Social Web. Hence, the time is right to exploit and improve such technologies for connecting user and usage data traces on the Social Semantic Web. Linking distributed traces of user data provides new possibilities for inferring and modeling user preferences and personalizing Web systems to individual needs. Novel models, techniques, frameworks and systems have to be developed to leverage Social Web semantics. While linkage of user and usage data promises advantages for recommendation and personalization, it also raises questions related to provenance, trust and privacy: how does one know that the data gathered from several sources can be trusted, and how can one avoid that sensitive personal data is disclosed to certain services or used to infer and expose sensitive information? Trust and privacy, and associated policies, may therefore impact mining and reasoning on the people's data. Topics ========= This special issue presents latest research developments on user data in the Social Semantic Web from both angles: (1) techniques and applications for linking, reusing and mining user and usage data and exploiting such data to personalize Social Web experiences, as well as (2) trust and privacy techniques and their impact on society. In particular, we seek for contributions addressing the following topics. + People's Data on the Personal and Social Semantic Web: - Analyses of user data and usage logs distributed on the Web - Capturing the semantics of user interactions - Inferring semantics from user data and usage logs - Linkage, aggregation and integration of distributed user/usage data - Linked Open Data in the Personal and Social Web - Representing and enriching user and usage data - Authorization and access control mechanisms for user/usage data - Methods, techniques and formats for trust-enabled sharing user and usage data (with provenance awareness) - Data collections and services for Personal and Social Semantic Web + Applications that leverage People's Data on the Personal and Social Semantic Web: - Personalization and adaptation of Social Semantic Web applications - Recommender systems and personalized search on the Social Semantic Web - Personalization and adaptation approaches that benefit from analysis of social data - Mining user data streams and mining heterogeneous data sources - Intelligent and adaptive user interfaces for user/usage data - Interoperability of applications, data sources and services - Semantic techniques for trust and privacy in social networks - Supporting awareness for user/usage data distributed on the Web - Scalability and robustness of Social Semantic Web systems Submissions ============== High-quality papers containing original research results on the above and related topics are solicited. Extended versions of papers previously published in conferences and workshops are also welcome, given that they are substantially expanded and improved. Authors should submit a manuscript (in IOS Press format) through the Semantic Web Journal on-line system, following the guidelines available at: http://www.semantic-web-journal.net/authors. Please mention the title of this special issue in the submission. All submissions will undergo an open review process, according to the standards of the Semantic Web Journal: http://www.semantic-web-journal.net/reviewers#review Important Dates ================= Submission deadline: 01 July 2011 Notifications: 02 September 2011 Camera-ready version: October 2011 Publication: November 2011 Guest Editors ================ Fabian Abel Delft University of Technology, The Netherlands http://www.st.ewi.tudelft.nl/~abel/ f.abel@tudelft.nl Laura Hollink Delft University of Technology, The Netherlands http://www.st.ewi.tudelft.nl/~hollink/ l.hollink@tudelft.nl Geert-Jan Houben Delft University of Technology, The Netherlands http://www.st.ewi.tudelft.nl/~houben/ g.j.p.m.houben@tudelft.nl Guest Editorial Board ========================================== - Lora Aroyo (Vrije Universiteit, Amsterdam, the Netherlands) - Bettina Berendt (K.U. Leuven, Belgium) - Dan Brickley (Vrije Universiteit, Amsterdam, the Netherlands) - Francesca Carmagnola (University of Torino, Italy) - Federica Cena (University of Torino, Italy) - Vania Dimitrova (University of Leeds, UK) - Olaf Hartig (Humboldt-Universiaet zu Berlin, Germany) - Eelco Herder (L3S Research Center, Germany) - Andreas Hotho (University of Wuerzburg, Germany) - Vera Hollink (CWI Amsterdam, Netherlands) - Daniel Krause (Leibniz University Hannover, Germany) - Knud Moeller (DERI/NUIG, Ireland) - Claudia Mueller-Birn (FU Berlin, Germany) - Andreas Nauerz (IBM Research, Germany) - Alexandre Passant (DERI, Ireland) - Matthew Rowe (The Open University, UK) - Ansgar Scherp (University of Koblenz-Landau, Germany) - Sergej Sizov (University of Koblenz-Landau, Germany) - David Vallet (Universidad Autonoma de Madrid, Spain) |
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