Publication

Semantic Social Collaborative Filtering with FOAFRealm

Kruk, Sebastian Ryszard
; 
Decker, Stefan
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http://hdl.handle.net/10379/501
 https://doi.org/10.13025/21347
Publication Date
2005
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Workshop paper
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Citation
Sebastian Ryszard Kruk, Stefan Decker "Semantic Social Collaborative Filtering with FOAFRealm", Proceedings of the Semantic Desktop Workshop, in conjunction with ISWC 2005, 2005.
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.
Funder
Science Foundation Ireland
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Attribution-NonCommercial-NoDerivs 3.0 Ireland
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Data Science Institute (Workshop Papers)