A Collaborative Filtering Recommendation Algorithm Based on User Trust Model
Jia Yubo, Hao Cai, Huang Chengwei · 2010
Collaborative filtering is one of the most successful recommendation technology, which has been widely used in e-commerce recommendation, and it uses the ratings of users who have similar behavior with target user to generate recommendation. However, our research reveals that the traditional collaborative filtering algorithms emphasis on the role of similarity too much, which is a contrary to our cognition. In this paper, we introduce the mechanism of trust which is mature in sociology to improve the traditional algorithm. The experiment result shows that our algorithm is efficient since it has higher accuracy compared with the traditional collaborative filtering.