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改进k-means 算法在电信CRM 客户分类中的应用
引用本文:左国才,周荣华,黎自强. 改进k-means 算法在电信CRM 客户分类中的应用[J]. 计算机系统应用, 2012, 21(11): 153-155,186
作者姓名:左国才  周荣华  黎自强
作者单位:湖南软件职业学院软件工程系,湘潭411100
基金项目:湖南省教育厅科学研究项目(11C0724,11C0723)
摘    要:电信市场的竞争在于客户的竞争,为了在激烈的竞争中保持优势,必须将客户进行细分,针对不同的客户,研究出相应的营销策略.K-means算法能对大型数据集进行高效分类,但对“噪声”敏感,聚类结果不准确,本文对该算法进行改进,使其能够实现更加准确和全面的客户细分.

关 键 词:电信CRM  客户细分  数据挖掘  K-means聚类分析算法
收稿时间:2012-03-19
修稿时间:2012-05-01

Improved K-Means Algorithm and Its CRM in Telecom Customer Segmentation Application
ZUO Guo-Cai,ZHOU Rong-Hua and LI Zi-Qiang. Improved K-Means Algorithm and Its CRM in Telecom Customer Segmentation Application[J]. Computer Systems& Applications, 2012, 21(11): 153-155,186
Authors:ZUO Guo-Cai  ZHOU Rong-Hua  LI Zi-Qiang
Affiliation:(Software Engineering, Hunan Vocational Institute of Software, Xiangtan 411100, China)
Abstract:The telecommunication market competition is the competition for customers, in the fierce competition to maintain advantage, must be customer segmentation, for different customers, work out the corresponding marketing strategy. K-means algorithm for large data sets for efficient classification, but the " noise" sensitive, clustering result is not accurate, the algorithm is improved, which can achieve a more accurate and comprehensive customer segmentation.
Keywords:telecommunication CRM  customer segmentation  data mining  clustering analysis of K-means algorithm
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