Automatic Clustering Algorithm for Movie Recommendation Based on LFM Model

In order to enhance audience satisfaction and recommend them different types of movies, it is necessary to point out the concept, latent factor model (hereinafter referred to as LFM). By using clustering analysis technology, users can be divided into different clusters according to the similarity principle, and then according to the evaluation information of the users in the same cluster. LFM algorithm based on the user's behavior to generate implicit feedback, automatic clustering of the user's interest in the class and the hidden category. Because the clustering process can be carried out offline, the clustering process does not affect the response speed of the recommendation system. The figures show that audience will classify the movies automatically. Experiments have showed that the method is effective and accuracy.