Research on Recommendation Algorithm Based on Collaborative Filtering

In view of the many shortcomings of the current industry recommendation system, this article has carried out meaningful and valuable in-depth research and exploration on the collaborative filtering recommendation algorithm [1] [2] adopted by the personalized news recommendation system, hoping to help users accurately from the huge amount of news ocean Quickly find interesting news and get a good user experience. The main tasks of this paper are: 1) Conduct an in-depth study and review of related technologies for personalized news recommendation. 2) Propose an improved collaborative filtering recommendation algorithm based on user item hybrid model. 3) Design and implement a personalized news recommendation system [3] [4] based on a collaborative filtering recommendation algorithm based on an improved user item hybrid model [5]. The experimental data proves that this system has a good personalized recommendation function, and the personalized news recommendation system based on this algorithm is more effective. The recommendation effect of the traditional personalized recommendation system has been significantly improved.