Design and Realization of Personalized Service in Electronic Commerce

摘要：

Classical collaborative filtering recommendation is the most successful recommendation algorithm in electronic commerce system application. However, along with the continuous increase of site structure, content complexity and user number, data is extremely sparse and the real-time property and recommendation accuracy of algorithm decrease significantly, even no any commodity can be recommended. This paper classifies the users in electronic commerce by collaborative clustering and carries out different page recommendations for different types of users to realize the personalized service in electronic commerce.

关键词： electronic commerce collaborative clustering personalized service

作者: Liu Xiao-liang

作者单位: Dept. of BusinessHebei University of Economics and Business Shijiazhuang, Hebei

会议类型: 国际会议

会议名称: 2009 2nd IEEE International Conference on Computer Science and Information Technology(第二届计算机科学与信息技术国际会议 ICCSIT2009)

会议地点: 北京

会议语种:英文

页码: 1977-1981

在线出版日期: 2009-08-08（万方平台首次上网日期，不代表论文的发表时间）