An Intelligent E-Commerce Recommendation Algorithm Based on Collaborative Filtering Technology

This paper presents an intelligent E-commerce recommendation algorithm with collaborative filtering algorithm. Firstly, a novel user interest model is given, which is an important module in the E-commerce recommendation system. Particularly, to effectively integrate the user interest model with collaborative filtering algorithm, we assume that if two users have similar interest vector, they may want to choose the same products. Furthermore, we define the users with similar interests as neighbor, and finding the neighbors is of great importance in the E-commerce recommendation. Secondly, the intelligent E-commerce recommendation algorithm is proposed based on user-rating matrix, and the products with highest scores is recommendated to the target user. Finally, experiments are conducted to make performance. Compared with other two schemes using four metrics, it can be seen that the proposed algorithm is more suitable to be used in E-commerce recommendation system.