CLUSTERING ANALYSIS OF ELECTRONIC COMMERCE CUSTOMERS BASED ON FUZZY SET
With the development of the Intemet,more and more commerce conducts and transactions are taken place on Web.Electronic commerce is now ubiquitous and the number of electronic customers increases quickly.So many customers contain abundant information,it is necessary to classify the customers and find the excellent customers, also this work is difficult.In customers clustering analysis, the key problems to be solved include how to measure clustering conducts and general standards.Because of the noise information,it is important to reduce the noise data in customer information.In this paper, a new algorithm of customers clustering is proposed based on fuzzy set. It takes account of the multilevel index and relationship in different attributions.The algorithm can decrease the noise data in customer classification.Because of the unrestricted classification attributions, the algorithm can be applied in other fields by modifying the classification attributions only.
Fuzzy Set Electronic Commerce Clustering Analysis Membership Function
Hongxin Wan Yun Peng
Mathematics & Computer Science College,Jiangxi Science & Technology Normal University Nanchang 33001 College of Computer Information and Engineering,Jiangxi Normal University Nanchang 330022,P.R.China
国际会议
2009 International Symposium on Computer Science and Technology(2009 中国宁波国际计算机科学与技术学术大会)
宁波
英文
365-367
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）