关键词: 领域敏感度, 信任关系, 概率矩阵分解, 社会化推荐

Abstract: Most of the trust-aware recommendation methods think that all friends with trust relationship have an impact on user ratings, which ignores the diversity of trust and the change of user interest with the field. This paper proposes a social recommendation algorithm based on domain-sensitive interest circle DSC-PMF. The DSC-PMF algorithm uses the Domain-Sensitive Interest Circle（DSC） model and a Probabilistic Matrix Factorization（PMF） strategy to recommend items to users in a specific domain. The DSC model only considers the influence of friends with similar interests, and measures the influence of different friends by decomposing trust value. It also defines “the user’s domain sensitivity” to assess different willingness to be influenced. According to the experimental results on the Yelp datasets, the proposed algorithm not only reduces MAE and RMSE, but also improves the recommendation accuracy of the system.

Key words: domain sensitivity, trust relationship, probabilistic matrix factorization, social recommendation