计算机技术与发展2011，Vol.21Issue(6)：63-65,69,4.
改进K-means算法实现移动通信行为特征分析
Application of Improved K-Means Algorithm in Mobile Communication Behavioral Characteristic Analysis
摘要
Abstract
K-means algorithm is widely used to customer segmentation clustering application research, customer segmentation of mobile communications has important commercial value. But dimensionunit, dimension of variable, cluster numbers, initial centroids,etc. calculation of these parameters is important factor of influencing K-means algorithm cluster application result. Based on K-means algorithm mobile communication behavior characteristic analysis process of implementing, respectively from the characteristic dimensions selection,variable dimensionunit unity, cluster number K value and initial centroids determination four aspects, improve the determination of the above algorithm affects parameters calculation method, utilize experience weighting way to make algorithm bind with subjective experience. The result of study indicates that according to behavioral characteristic analysis improving K-means algorithm will subdivide the cluster to the mobile communication customer effectively.关键词
客户细分/K-means/影响因子Key words
customer segmentation/ K-means/ influencing factor分类
信息技术与安全科学引用本文复制引用
何云,李辉,姚能坚,赵榕生..改进K-means算法实现移动通信行为特征分析[J].计算机技术与发展,2011,21(6):63-65,69,4.基金项目
广空预研项目(GK2009BE0102) （GK2009BE0102）
