基于K-means聚类算法的校园网用户行为分析研究  

Research of Customer Behavior Analysis In Campus Network Based on K-means Clustering Algorithm

作　　者：丁青[1] 周留根[2] 朱爱兵[1] 张义东[1] 

机构地区：[1]南京农业大学工学院网络中心,南京210031 [2]南京农业大学研究生院,南京210095

出　　处：《微计算机应用》2010年第6期74-80,共7页Microcomputer Applications

基　　金：江苏省农机局科研启动基金(GXS06016)

摘　　要：利用数据挖掘相关技术,针对后台计费服务器的数据库,基于K-means算法以校园网用户行为特征为对象来进行聚类分析,提出了几个校园网用户行为分析的模型。此类模型为校园网管理者在制定有效管理策略,满足校园网用户个性化需求方面提供理论依据。The paper presents some models for customer behavior analysis of campus network based on data mining technology, which is constructed by clustering analysis of background charging server database with behavior characteristic of high - school customers based on K- means algorithm. The model can provide good theoretical support for network administrators to design effective management strategy to meet individual requirements of high- school customers.

关 键 词：用户行为 聚类 K—means 

分 类 号：TP393.18[自动化与计算机技术—计算机应用技术]