聚类算法在B2C电子商务客户细分中的应用  

The Applications of Clustering in the Customer Segmentation of B2C E-Commerce

作　　者：郭媛香[1] 

机构地区：[1]晋中学院,山西晋中030600

出　　处：《忻州师范学院学报》2009年第2期27-29,共3页Journal of Xinzhou Teachers University

基　　金：山西省2008年度高校科技开发项目"Web使用挖掘在B2C电子商务中的应用研究"(20081047)

摘　　要：B2C电子商务的竞争对个性化服务提出更高的要求,聚类分析是在数据挖掘的基础上,根据Web用户的行为模式,将具有相似属性的用户分为一簇。最大最小距离算法按照某种策略,选取离得尽可能远的客户作为初始中心,努力得到客户群一个比较好的初始划分,显著提高聚类质量,为电子商务企业了解客户、挖掘客户、制定营销策略,提供有力帮助。B2C e -commerce competition has made higher requirements for personalized services. The cluster analysis divided similar attribute users into a cluster according to the Web user＇s behavior patterns on the basis of data searching. The maximum and minimum distance are counted in accordance with some strategy, taking customers as far as possible as the initial center to get a better initialization points about customer base and remarkably improve the quality of the clustering, which provides e - commerce enterprises powerful help in understanding customers, finding customers, and making marketing strategies.

关 键 词：聚类算法 电子商务 客户细分 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]