PocketLens: Toward a personal recommender system
ACM Transactions on Information Systems (TOIS)
A Client/Server User-Based Collaborative Filtering Algorithm: Model and Implementation
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Overlay management for fully distributed user-based collaborative filtering
EuroPar'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part I
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Using structural information for distributed recommendation in a social network
Applied Intelligence
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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.