社会网络环境下基于信任传递的推荐模型研究

Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》

陈文俊 倪静

Abstract： The current trust-based recommendation algorithms did not fully exploit the trust relationship between users and it lacked reasonable trust transitivity rules, which greatly affected the reliability and accuracy of the recommendation algorithm. Aiming at the above problems, this paper combined user rating data with the user's social relationship to build a trust transitivity model, and proposes a recommendation algorithm based on trust transitivity. Firstly, the algorithm uses the score data to calculate the implicit direct trust relationship of the users in the trust transitivity model. Secondly, the indirect trust relationship of multiple trust transitivity chains is solved by solving the ordered weighted average operator. Finally, it converge the user’s trust and similarity into comprehensive similarity for predictive recommendation. The experimental results show that the proposed algorithm can effectively improve the recommendation quality of the system.

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