Modeling Preferences in a Distributed Recommender System
Identifieur interne : 004C28 ( Main/Exploration ); précédent : 004C27; suivant : 004C29Modeling Preferences in a Distributed Recommender System
Auteurs : Sylvain Castagnos [France] ; Anne Boyer [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: A good way to help users finding relevant items on document platforms consists in suggesting content in accordance with their preferences. When implementing such a recommender system, the number of potential users and the confidential nature of some data should be taken into account. This paper introduces a new P2P recommender system which models individual preferences and exploits them through a user-centered filtering algorithm. The latter has been designed to deal with problems of scalability, reactivity, and privacy.
Url:
DOI: 10.1007/978-3-540-73078-1_53
Affiliations:
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When implementing such a recommender system, the number of potential users and the confidential nature of some data should be taken into account. This paper introduces a new P2P recommender system which models individual preferences and exploits them through a user-centered filtering algorithm. 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