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.
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)
关键词
用户行为
聚类
K—means
data - mining, customer behavior, clustering algorithm, K - means
