Research on the Recommending Method Used in C2C Online Trading

Electronic commerce becomes more and more frequent and the online trading bases on C2C context are more common. However, the ever-increasing user size and commodities cause the problem of information overload. Collaborative filtering technology is the most popular and successful method to overcome the problem in E-commerce recommender systems. Since there is much difference between B2C and C2C context where not only the buyer preference but also the seller preference is taken into account . This paper analyzes the user behaviors on the website and constructs the user preference model under the C2C context. And the author defines trust vector in this paper. Based on this definition, a new recommend trust model is proposed. The simulation shows that compared with the current recommending method, the proposed one is more effective.