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A scalable P2P recommender system based on distributed collaborative filtering
2004
Expert systems with applications
Collaborative Filtering (CF) technique has been proved to be one of the most successful techniques in recommender systems in recent years. However, most existing CF based recommender systems worked in a centralized way and suffered from its shortage in scalability as their calculation complexity increased quickly both in time and space when the record in user database increases. In this article, we first propose a distributed CF algorithm called PipeCF together with two novel approaches:
doi:10.1016/j.eswa.2004.01.003
fatcat:mc57fncuw5bftgl7744zqzfhri