基于用户特性的Web会话模式聚类算法  

A CLUSTERING ALGORITHM FOR WEB SESSION PATTERN BASED ON USERS' CHARACTERISTICS

作　　者：郑富兰[1] 吴瑞[1] 

机构地区：[1]山西师范大学数学与计算机科学学院,山西临汾041004

出　　处：《计算机应用与软件》2014年第2期283-286,共4页Computer Applications and Software

基　　金：国家自然科学基金项目(70802043);山西省自然科学基金项目(2008011029-2)

摘　　要：Web用户聚类是通过分析用户会话,将具有相同或相似访问特征的用户聚为一类。在会话相似性度量方面综合考虑了网页浏览时间和访问频次两个因素,并考虑到用户个人习惯、能力等因素对浏览时间的影响,将浏览时间处理为RDP(Reduce the Differences in Personality)浏览时间,以降低其个性特征。为此,提出一种基于用户特性的RDPk-means聚类算法。实验表明,该算法可以有效实现用户会话的聚类,聚类结果客观合理。The Web users’clustering is to group the users with same or similar surfing behaviour into one class by analysing their ses-sions.In this paper,two factors of browsing time on webpage and visiting frequency are synthetically considered in sessions’similarity met-ric.In addition,the influence of other factors such as personal habit and ability on browsing time has also been taken into account.Browsing time is processed as RDP browsing time so as to reduce its personality characteristics.Therefore,we propose a personality characteristics-based RDPk-means clustering algorithm.Experiments show that this algorithm is effective in realising users’sessions clustering,the cluste-ring results are objective and reasonable.

关 键 词：WEB挖掘 WEB用户聚类 聚类算法 模式聚类 K-MEANS 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]