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dc.contributor.authorKruk, Sebastian Ryszarden
dc.contributor.authorDecker, Stefanen
dc.date.accessioned2009-12-11T10:15:16Zen
dc.date.available2009-12-11T10:15:16Zen
dc.date.issued2005en
dc.identifier.citationSebastian 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.urihttp://hdl.handle.net/10379/501en
dc.description.abstractThe 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.formatapplication/pdfen
dc.language.isoenen
dc.subject.lcshRecommender systems (Information filtering)en
dc.subject.lcshInformation filtering systemsen
dc.subject.lcshComputer securityen
dc.subject.lcshOnline social networksen
dc.titleSemantic Social Collaborative Filtering with FOAFRealmen
dc.typeWorkshop paperen
dc.description.peer-reviewedpeer-revieweden
dc.contributor.funderScience Foundation Irelanden
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