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Application of clustering on credit card customer segmentation based on AHP

机译:聚类在基于层次分析法的信用卡客户细分中的应用

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It has been crucial for credit card operators to conduct targeted marketing with effective customer segmentation recently years. The clustering analysis of data mining technology is the most effective tool for this, and the selection of indicators means a lot on the results of segmentation in the meanwhile. In this paper, we select two algorithms, AHP (Analytical Hierarchy Process) for indicator optimization, and K-means for clustering. Based on briefly theoretical analysis of the algorithms, we carry out a case study using the data of credit card customers from a commercial bank of Shanghai, and develop the corresponding marketing strategies, possessing certain theoretical value and practical significance.
机译:近年来,对于信用卡运营商而言,进行有效的客户细分来进行有针对性的营销至关重要。数据挖掘技术的聚类分析是实现这一目标的最有效工具,而指标的选择对分割结果具有重要意义。在本文中,我们选择两种算法:用于指标优化的AHP(分析层次过程)和用于聚类的K-means。在对算法进行简要理论分析的基础上,以上海某商业银行信用卡客户数据为例进行了案例研究,制定了相应的营销策略,具有一定的理论价值和现实意义。

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