%0 Journal Article
%T Customer Data Mining for Supporting Cross-Marketing of Financial Products<br>支持交叉营销的金融产品客户数据挖掘
%A HUANG Hong
%A HONG Yi
%A <br>黄洪
%A 洪毅
%J 计算机系统应用
%D 2010
%I 
%X 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.
%K cross-marketing
%K X-means clustering algorithm
%K customer segmentation
%K financial product marketing<br>交叉营销
%K X-means聚类算法
%K 客户细分
%K 金融产品营销
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=0F955061DB6FF943CECCA390BA575A9A&yid=140ECF96957D60B2&vid=2A8D03AD8076A2E3&iid=94C357A881DFC066&sid=8C83C265AD318E34&eid=89F76E117E9BDB76&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=7