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.
出处
《微计算机信息》
北大核心
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
关键词
粗糙集
相似分类
客户分类管理
rough sets
slmilarity classification
customer-classified management
