关键词: 推荐系统, 协同过滤, 相似度, 分段

Abstract: With the rapid development of the Internet, a large variety of information has exploded, and resulting in information overload. Now, by analyzing a large number of available information, recommender systems can help users find things they are interested. And collaborative filtering is the most widely used approach in the recommendation systems. However, its accuracy of recommendation is still needed to be improved. In this paper, a novel effective collaborative filtering algorithm based on segmented and improved PCC is proposed to improve the accuracy of the recommendation system. The number of co-items and the PCC threshold is used to calculate and improve the results of the PCC in this method. Finally, the experimental results show that the proposed method is better than other traditional methods.

Key words: recommender system, collaborative filtering, similarity, segmentation