基于相似粗糙集的客户分类管理研究  

Study of Customer-Classified Management Based on Similar Rough Sets

作　　者：王旅 彭宏[2] 胡劲松[2] 

机构地区：[1]湛江市电视大学,广东省524003 [2]华南理工大学计算机科学与工程学院

出　　处：《微计算机信息》2006年第05X期147-149,共3页Control & Automation

基　　金：广东省科技攻关项目(A10202001);广州市科技攻关项目(2004Z2-D0091)资助

摘　　要：Pawlak粗糙集理论在分类挖掘中得到了广泛应用,基于相似粗糙集的分类挖掘算法是传统粗糙分类方法的拓展,可以用于在数值型决策表中发现分类规则。客户分类管理是CRM的核心内容之一,科学有效的客户分类管理对于一个企业具有重要的意义。本文阐述了基于相似粗糙集的分类算法及其客户分类应用实例,分类结果表明了该分类方法的有效性。Rough set theory introduced by Pawlak is widely applied in classification mining. Similarity classification mining based on rough sets is an expanding method of traditional rough classification, and it can be used for finding classification rules in the numeric type decision table. Customer-classified management is one of the core content of CRM. It is of important meaning for an enterprise to classify customer validly and efficiently. This paper presents the classification algorithm based on similar rough sets and its application in customer-classified management. The result shows that the classification method is effective.

关 键 词：粗糙集 相似分类 客户分类管理 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]