Abstract: Data sparsity is one of the major challenges faced by collaborative filtering.Trust relationships between users provide useful additional information for the recommender system.In the existing studies,the direct trust relationships are mainly used as additional information,while the indirect trust relationships are less considered.This paper proposed a recommendation algorithm(ATRec) that combines the direct and indirect asymmetric trust relationships.First,a trust transfer mechanism is constructed and used to obtain asymmetric indirect trust relationships between users.Second,each user’s trust set is obtained by the direct and indirect asymmetric trust relationship.At last,the popularity of the item is computed according to the rating information of the trust set or the k-nearest neighbors and the favorable thre- shold,thus generating user’s top-N recommendation list by the recommended threshold.The experimental results show that this algorithm has better performance than the state-of-the-art recommendation algorithms in top-N recommendation.

Key words: Asymmetric trust relationship, Personalized recommendation, Recommender system, Trust transfer mechanism