An Improved Personalized E-commerce Recommendation System based on Fuzzy ART
This paper using Fuzzy ART algorithm to improve the quality and the efficiency of Cluster-based collaborative filtering recommended methods for ecommerce. The proposed algorithm processes adaptive learning and improves the recommend quality. Meanwhile, according to the sparsity of data and cold start problem, this paper improves the Fuzzy ART algorithm with the content based recommendation method. Finally, considering the influence of user information to the recommendation quality, the proposed recommendation method is superior among the existing methods.
Personalized Recommendation Fuzzy ART User Based Recommendation Content-based recommendations-commerce Recommendation System
Fuliang XUE
School of Business.Tianjin University of Finance & Economics,TianJin.China
国际会议
太原
英文
495-498
2011-02-26（万方平台首次上网日期，不代表论文的发表时间）