Improved Recommendation Algorithm Based on Clustering and Association Rule

摘要：

Recommender systems apply knowledge discovery techniques to the problem of making products recommendations during a live customer interaction and they are achieving widespread success in ecommerce nowadays. But the traditional recommendation algorithm makes the quality of system decreased dramatically. In particular,we present a improved recommendation algorithm based on clustering and association rule to calculate the customers nearest neighbor,and then provide the most appropriate products to meet his needs. The experimental results show the efficiency of our method.

关键词： Recommendation algorithm Clustering Associate rule

作者: Bing Xu JianPing Ma YongHai Yu

作者单位: Zhejing University of Technology,P.R.China

会议类型: 国际会议

会议名称: 2011 International Conference on Opto-Electronics Engineering and Information Science(2011光电电子工程与信息科学国际会议 ICOEIS 2011)

会议地点: 西安

会议语种:英文

页码: 2658-2660

在线出版日期: 2011-12-23（万方平台首次上网日期，不代表论文的发表时间）