Modeling Preferences in a Distributed Recommender System
Résumé
A good way to help users finding relevant items on docu- ment 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.
Domaines
Intelligence artificielle [cs.AI]Origine | Fichiers éditeurs autorisés sur une archive ouverte |
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