计算机工程与科学2009，Vol.31Issue(12)：74-76,3.DOI:10.3969/j.issn.1007-130X.2009.12.022
一种结合PSOA的模糊K-均值客户聚类算法
A Fuzzy K-Means Customer Clustering Algorithm Combined with PSOA
摘要
Abstract
Applying the fuzzy means clustering algorithms combined with PSO to the customer-clustering analysis in CRM is a new research field. This paper proposes an algorithm in which N keywords which appear most frequently in M customers are regarded as the features of the customers. The features of M customers compose a pattern sample set for fuzzy customer-clustering. The Particle Swarm Optimization algorithm is embedded into the fuzzy K-mean clustering algorithm so as to optimize the total scattering degree of clusters to be minimum and obtain the optimization of customer clusters. The results of experiments indicate that the algorithm can obtain better clustering results for the customer-clustering problems.关键词
模糊K均值聚类/粒子群优化算法/客户聚类/客户关系管理Key words
fuzzy K-means clustering/PSO algorithm/customer clustering/CRM分类
信息技术与安全科学引用本文复制引用
朱沅海,林泉,万杰..一种结合PSOA的模糊K-均值客户聚类算法[J].计算机工程与科学,2009,31(12):74-76,3.基金项目
湖南省自然科学基金资助项目(07JJ3120) （07JJ3120）
湖南省科技计划资助项目(08GK3085) （08GK3085）
湖南省教育厅资助项目(08C102) （08C102）
