社会网络环境下基于信任传递的推荐模型研究.

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 proposed a recommendation algorithm based on trust transitivity. Firstly, the algorithm used the score data to calculate the implicit direct trust relationship of the users in the trust transitivity model. Secondly, it solved the indirect trust relationship of multiple trust transitivity chains 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. [ABSTRACT FROM AUTHOR]