… We propose a fully decentralized collaborative filtering approach that is self … tested and compared our distributed collaborative filtering approach to centralized collaborative filtering and showed that it has similar performance …

… Commerce is collaborative filtering which is based on the ratings of other customers who have similar preferences. However, collaborative filtering may not provide … for collaborative filtering. The algorithm uses the K-Means Clustering method …

… The increasing users and items restrict the development of collaborative filtering recommendation systems. Then a series of problems, such as sparsity, cold start and scalability, come out. In this paper, we add user preference based …

… The growth of Internet commerce has stimulated the use of collaborative filtering (CF) algorithms as recommender systems. Such systems leverage knowledge about the known preferences of multiple users to recommend items of interest …