支持交叉营销的金融产品客户数据挖掘  

Customer Data Mining for Supporting Cross-Marketing of Financial Products

作　　者：黄洪[1] 洪毅[1] 

机构地区：[1]浙江工业大学软件学院,浙江杭州310023

出　　处：《计算机系统应用》2010年第5期100-103,共4页Computer Systems & Applications

摘　　要：首先比较了DBSCAN,CLIQUE,CLARANS,K-means和X-means等聚类算法,接着选用X-means聚类算法建立了金融产品客户细分模型,然后结合关联强度分析,设计了支持交叉营销的金融产品客户数据挖掘系统,并给出了一个系统使用示例。This paper makes a comparison between Clustering algorithms such as DBSCAN, CLIQUE, CLARANS, K-means and X-means. The X-means clustering algorithm is selected to establish a customer segmentation model for financial products marketing. Based on relational analysis of financial products, a financial products customer data mining application system is designed to support the cross-marketing of financial products. In the end, a use case is given to illustrate the application of the system.

关 键 词：交叉营销 X—means聚类算法 客户细分 金融产品营销 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]