UR: A User-Based Collaborative Filtering Recommendation System Based on Trust Mechanism and Time Weighting

The technology of personalized recommendation is aimed at studying the behaviors of users, analyzing what they may be interested in and recommending suitable items to them. In other words, the personalized recommendation is to better solve the contradiction between the requirements of users and the explosive information on the Internet. The userbased collaborative filtering recommendation is one of the most successful technology for recommendation system. The most significant step of user-based collaborative filtering recommendation is comprehensive user similarity calculation. However, most recommendation systems ignore the indispensability of trust mechanism of the users and the time weighted users rating attributes in user similarity calculation, which leads to the inaccurate recommendation. Based on these issues, this paper proposes an optimized user-based collaborative filtering recommendation systemcalled UR. UR not only validates the necessity of the trust mechanism of the users and the time weighted users rating in the comprehensive user similarity calculation, but also improves the recommendation accuracy