关键词: 推荐系统, 社交网络, 贝叶斯网络, 信任驱动

Abstract: To deal with the problems such as the source intricacy of recommendation behaviors, path diversity, distrusting strangers’ recommendation, a trust-driven recommendation method in social networks is proposed. The method uses Bayesian network, calculates the prior probability distribution of users’ scores and the joint conditional probability between the friends, predicts users’ ratings in the environment and provides the appropriate recommendations for the users. In the process of trust-driven recommending, rating prediction takes into account not only users’ preference, but also users’ social relationships; in addition, the information exchanges of the users are limited between friends, which can effectively protect the user privacy. Experimental results show that the proposed recommendation method has good performance on prediction accuracy and recommend coverage.

Key words: recommender system, social network, Bayesian network, trust driven