聚类数据挖掘在商场顾客分析中的应用  

The Application of Clustering Data Mining in Customer Analysis of the Department Store

作　　者：罗妤[1] 余力 

机构地区：[1]重庆科技学院电子信息工程学院,重庆400050 [2]中国网通集团重庆市分公司,重庆400039

出　　处：《自动化技术与应用》2007年第9期34-36,共3页Techniques of Automation and Applications

摘　　要：数据挖掘用于从大量数据中发现知识,提供决策支持。本文对聚类数据挖掘应用于商场顾客分析的实现问题进行了研究。基于重庆两百商场OLTP数据库,构建了数据仓库,针对商场顾客群特征,以及顾客特征与购买商品类别之间的关系问题,建立了两个聚类数据挖掘模型,并对数据挖掘结果进行了分析。Data mining is used for knowledge discovering from mass data to support decision making. The implementation aspects of applying clustering data mining method to customer analysis of the department store are discussed in this paper. A data warehouse is built based on the OLTP database of the Chongqing Liangbai Department store. Two data mining models of customer characteristics and the relationship between the customer and the product categories are established.

关 键 词：数据仓库 数据挖掘 聚类分析 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]