Customer Data Mining for Supporting Cross-Marketing of Financial Products
支持交叉营销的金融产品客户数据挖掘

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.