关键词: 推荐系统, 协同过滤, 社交网络, 信任模型

Abstract: The recommendation system plays a significant role in dealing with the information overload problem, but the recommendation system also has its disadvantages in terms of its data sparsity and cold start problems. Using traditional collaborative filtering algorithms can no longer satisfy the technical development of the recommendation system. With the development of social networks, the trust relationship of friends has been widely used in the recommendation system. However, in real life, the trust relationship in social networks also has the problem of sparse data. In order to better improve the quality of recommendations, a collaborative filtering recommendation algorithm for integrating potential social trust models is proposed. The new social trust model is mainly composed of the following parts：global trust values and expert models in the social matrix, an improved trust propagation model, an improved Pearson coefficient model. Through the analysis of the experimental results, it is known that the recommended algorithm for the fusion of the new model helps to improve the recommendation effect.

Key words: recommendation system, collaborative filtering, social network, trust model