首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于人工蚁群的Web会话聚类
引用本文:周海斌.基于人工蚁群的Web会话聚类[J].重庆邮电学院学报(自然科学版),2006,18(5):657-659.
作者姓名:周海斌
作者单位:广西大学招生就业指导中心,广西壮族自治区南宁530004
摘    要:将改进的蚁群聚类算法应用于Web使用挖掘中,可对Web事务进行聚类,以便了解Web用户的兴趣以及它们之间的联系,从而为用户提供个性化的服务。同时定义一个Web会话为一个带权值的多维向量,也定义了两个会话间的相似度度量。实验表明在广西大学网站抽取的会话数据集上执行蚁群聚类算法得到的聚类是稳定的。结果显示该算法执行得很好,能找到没有噪音的聚类。

关 键 词:Web  使用挖掘  人工蚁群  聚类
文章编号:1004-5694(2006)05-0657-03
收稿时间:2006-02-27
修稿时间:2006-09-11

Web sessions clustering based on artificial ants colonies
ZHOU Hal-bin.Web sessions clustering based on artificial ants colonies[J].Journal of Chongqing University of Posts and Telecommunications(Natural Sciences Edition),2006,18(5):657-659.
Authors:ZHOU Hal-bin
Institution:Instructing Center of Enrolling New Students and Obtaining Employment, Guangxi University, Nanning 530004, P. R. China
Abstract:In this paper,the author puts clustering algorithm into the application of Web usage mining for the clustering of Web affairs.By this way,the users' interests and the relations between them can be known,and then the personalized services will be provided.At the same time,the author defines a Web session as a weighted multi-dimension vector and also develops a similarity measure between two sessions.The experiment shows that the clusters gained by ant colony clustering algorithm are stable on a data set made of real sessions extracted from the Web site of the University of Guangxi.The result shows that this algorithm performs well and it is able to find non-noisy clusters.
Keywords:Web  usage miningl artificial ants  cluster
本文献已被 CNKI 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号