关键词: 推荐系统, 协同过滤, 用户项目偏好, 用户体验度, 长尾理论

Abstract: On the basis of the general user’s similarity calculation,a recommendation algorithm based on user project experience degree is proposed according to the impact of user preferences and project characteristics on user ratings.This paper describes the potential impact of the project experience degree on the user,and selects Pearson similarity formula for further calculation.Through the number of users praise for the projects accounting for the total number of project reviews and the proportion of the user’s rating to the overall project score,the user experience weight for the project is gained.The long tail theory is used to balance the user’s similarity and the user’s attention to the popular items.The user’s similarity is calculated,and the prediction and recommendation are generated.Experimental results show that,compared with the traditional collaborative filtering algorithm,the proposed algorithm improves the accuracy of similarity computation and the recommendation effect under sparse data.

Key words: recommendation system, collaborative filtering, user project preference, user experience degree, long tail theory