Customer segmentation and visualization by combination of self-organizing map and cluster analysis

Yohji Kameoka, Keita Yagi, Shohei Munakata, Yoshiro Yamamoto
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引用次数: 7

Abstract

To perceive the characteristics of customers from market information, it is necessary to aggregate the market information. So, we used a self-organizing map (SOM), arecency, frequency and monetary (RFM) analysis, and other methods to propose the classification of customers. In addition, we propose a visualization of the analysis results. In this study, we consider the combination of cluster analysis and the SOM for further consolidation of small clusters and visualization.
结合自组织图和聚类分析的客户细分和可视化
要从市场信息中感知顾客的特征,就需要对市场信息进行汇总。因此,我们使用了自组织图(SOM)、近代性、频率和货币性(RFM)分析等方法来提出客户分类。此外,我们提出了分析结果的可视化。在本研究中,我们考虑将聚类分析和SOM相结合,以进一步巩固小聚类和可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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