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Received:November 25, 2009 Revised:December 30, 2009
Received:November 25, 2009 Revised:December 30, 2009
中文摘要: 将自组织映射SOM(Self Organization Map)聚类算法应用于电信客户细分,并与采用K-means聚类算法得到的结果进行比较。实验表明,SOM可以有效的进行电信客户细分且聚类效果较优,但需付出训练时间的代价。同时对两种算法的复杂度、误差等进行了分析。
Abstract:This paper applies the SOM neural network to the customer segmentation of the telecommunication company, and compares the results of the K-means clustering algorithm and the SOM. The experiment indicates that the SOM is effective to classificate and the cluster effect is better when the data assemble is large, but it takes the training time. At the same time, it analyses the algorithm complexity and the errors of the two algorithms.
文章编号: 中图分类号: 文献标志码:
基金项目:安徽省自然科学基金(090416240);高等学校优秀人才基金(2009SQRS001ZD)
Author Name | Affiliation |
WU Chun-Xu | 中国科学技术大学 管理学院 安徽 合肥 230026 |
BAO Man-Yuan | |
GOU Qing-Long |
Author Name | Affiliation |
WU Chun-Xu | 中国科学技术大学 管理学院 安徽 合肥 230026 |
BAO Man-Yuan | |
GOU Qing-Long |
引用文本:
吴春旭,鲍满园,苟清龙.自组织映射聚类算法在电信客户细分中的应用①.计算机系统应用,2010,19(8):168-172
WU Chun-Xu,BAO Man-Yuan,GOU Qing-Long.Application of Self Organization Map to Classification of the Telecommunication Company.COMPUTER SYSTEMS APPLICATIONS,2010,19(8):168-172
吴春旭,鲍满园,苟清龙.自组织映射聚类算法在电信客户细分中的应用①.计算机系统应用,2010,19(8):168-172
WU Chun-Xu,BAO Man-Yuan,GOU Qing-Long.Application of Self Organization Map to Classification of the Telecommunication Company.COMPUTER SYSTEMS APPLICATIONS,2010,19(8):168-172