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Research on clustering analysis and its application in customer data mining of enterprise

机译:集群分析及其在企业数据挖掘中的应用研究

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The paper study improved K-means algorithm and establish indicators to classify customers according to RFM model. Experimental results show that, the new algorithm has good convergence and stability, it has better than single use of FKP algorithms for clustering. Finally, the paper studies the application of clustering in customer segmentation of mobile communication enterprise. It discusses the basic theory, customer segmentation methods and steps, the customer segmentation model based on consumption behavior psychology, and the segmentation model is successfully applied to the process of marketing decision support.
机译:本文研究了K-Means算法的改进,并建立指标以根据RFM模型对客户进行分类。实验结果表明,新算法具有良好的收敛性和稳定性,它优于单一使用FKP算法进行聚类。最后,本文研究了聚类在移动通信企业的客户分割中的应用。它讨论了基于消费行为心理学的基本理论,客户分割方法和步骤,客户分割模型,分割模型成功应用于营销决策支持的过程。

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