关键词: 主观信任, 全局声誉, 用户偏好, 专家优先信任

Abstract: Relying solely on the similarity to locate neighbor users has a serious negative impact on the performance of traditional collaborative filtering algorithm. Importing the trust mechanism in social networks, a model is built up from the perspective of individual’s subjective trust and global reputation in social circle. Direct trust is formed by considering users’ interactions, rating differences and preferences. Indirect trust can be generated by reputation and expert prior trust model. Then the proposed algorithm constructs the trust relationship among users through a dynamic weighting manner. The parameter η is introduced to coordinate double attributes including trust and similarity to make the user relationship more closer, which can solve the problems of new users as well as sparsity effectively. Pragmatic analysis reveals that the improved model has the remarkable results.

Key words: subjective trust, global reputation, user preferences, expert prior trust