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Recommendation systems are widely used by different user service providersspecially those who have interactions with the large community of users. Thispaper introduces a recommender system based on community detection. Therecommendation is provided using the local and global similarities betweenusers. The local information is obtained from communities, and the global onesare based on the ratings. Here, a new fuzzy community detection using thepersonalized PageRank metaphor is introduced. The fuzzy membership values ofthe users to the communities are utilized to define a similarity measure. Themethod is evaluated by using two well-known datasets: MovieLens and FilmTrust.The results show that our method outperforms recent recommender systems.

A Fuzzy Community-Based Recommender System Using PageRank