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Semantic Social Collaborative Filtering with FOAFRealm

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dc.contributor.author Kruk, Sebastian Ryszard en
dc.contributor.author Decker, Stefan en
dc.date.accessioned 2009-12-11T10:15:16Z en
dc.date.available 2009-12-11T10:15:16Z en
dc.date.issued 2005 en
dc.identifier.citation Sebastian Ryszard Kruk, Stefan Decker "Semantic Social Collaborative Filtering with FOAFRealm", Proceedings of the Semantic Desktop Workshop, in conjunction with ISWC 2005, 2005. en
dc.identifier.uri http://hdl.handle.net/10379/501 en
dc.description.abstract The most popular collaborative filtering implementations require either a critical mass of referenced resources and a lot of active users. Other solutions are based on finding a referral with an expertise on the given domain of discourse. In this article we present the semantic social collaborative filtering solution to information retrieval. We describe how the concept of users¿ managed collections can be exploited to provide collaborative filtering system based on social network maintained by the users themselves. We present FOAFRealm, a user profile management system based on the social networking and the FOAF metadata. FOAFRealm enables distributed collaboration between parties in the semantic social collaborative filtering way. en
dc.format application/pdf en
dc.language.iso en en
dc.subject.lcsh Recommender systems (Information filtering) en
dc.subject.lcsh Information filtering systems en
dc.subject.lcsh Computer security en
dc.subject.lcsh Online social networks en
dc.title Semantic Social Collaborative Filtering with FOAFRealm en
dc.type Workshop paper en
dc.description.peer-reviewed peer-reviewed en
dc.contributor.funder Science Foundation Ireland en

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