The Novel Model of Collaborative Filtering Recommendation Based on Fuzzy Clustering Analysis

Abstract

Collaborative filtering process is based on the known users of the evaluation of target users to predict the target of interest, and then to the target users to recommend new items. This paper applies the fuzzy clustering technology used in the project of nearest neighbors and the users nearest neighbor search, reduces the project space and user space calculation dimension, to improve the traditional collaborative filtering algorithm scalability. The paper puts forward the novel model of collaborative filtering recommendation based on fuzzy clustering analysis. Compared with the traditional method of item similarity calculation is more accurate, the experiments show that the method improves the accuracy of recommendation.