Collaborative Filtering Recommendation Algorithm Based on Clustering of User Interest Model

With the rapid development of e-commerce, collaborative filtering recommendation system has been widely used. In this paper, to address the low accuracy of identifying nearest neighbors and low real-time performance of recommendation in traditional collaborative filtering algorithms, the concept of user interest model is introduced. Based on clustering of user interest model, a collaborative filtering recommendation algorithm is proposed. The experimental results suggest that this algorithm can efficiently improve the accuracy of computing nearest neighbor and improve the real-time performance of recommendation system.