Modeling Preferences in a Distributed Recommender System

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.

• Type: Conference
• Year: 2007
• Where: UM
• Authors: Sylvain Castagnos, Anne Boyer
• Keywords: Models Individual Preferences, Recommender System, UM 2007, User-centered filtering Algorithm