关键词: 信任推荐, 协同过滤, 奇异值分解（SVD）, 推荐系统, 隐式信任

Abstract: To resolve the problems of data sparsity and cold-start of the collaborative filtering algorithms in recommender systems, the trust information has being introduced to recommender systems, it can effectively alleviate these problems above by adding the users’ explicit trust information. But the explicit trust information is more difficult to obtain or sparse, in order to better improve the efficiency of recommendation, in the basis of TrustSVD algorithm based on explicit trust, this paper introduces the implicit trust information, and proposes a singular value decomposition (SVD) algorithm based on double trust mechanism, named EITrustSVD. At the same time of getting a reliable recommendation by using the explicit trust, the EITrustSVD algorithm gets a recommendation related to user performance through implicit trust. The experimental results show that the proposed algorithm is a better solution to the problem of cold-start, and has a better recommendation accuracy.

Key words: trust recommendation, collaborative filtering, singular value decomposition (SVD), recommender systems, implicit trust