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路径聚类:在Web站点中的知识发现
引用本文:王实,高文,李锦涛,谢辉.路径聚类:在Web站点中的知识发现[J].计算机研究与发展,2001,38(4):482-486.
作者姓名:王实  高文  李锦涛  谢辉
作者单位:中国科学院计算技术研究所
基金项目:国家“八六三”高技术研究发展计划基金资助!(86 3-30 6 -JD0 6 -0 3-4 )
摘    要:用户对Web站点的访问代表了用对Web站点上页面的访问兴越,这种兴越程序可以通过用户对Web站点上页面的浏览顺序表现出来,在对Web站点的记问日志进行事务识别后,可以根据群体用户对Web站点的访问顺序进行聚类,即路径聚类,那么最终每一个聚类集就反映出该聚类集中的全体用户具有相似的访问兴越,为了得到这种根据用户访问兴越而对用户集的划分,提出了K-paths路径聚类方法,在这种方法中,根据用户的访问兴越定义了新的相似性测量手段和聚类中心,实验的结果是成功的。

关 键 词:数据挖掘  Web站点  知识发现  路径聚类  WWW  Internet

PATH CLUSTERING: DISCOVERING THE KNOWLEDGE IN THE WEB SITE
WANG Shi,GAO Wen,LI Jin-tao,XIE Hui.PATH CLUSTERING: DISCOVERING THE KNOWLEDGE IN THE WEB SITE[J].Journal of Computer Research and Development,2001,38(4):482-486.
Authors:WANG Shi  GAO Wen  LI Jin-tao  XIE Hui
Abstract:When users access a Web site, the access of the users represents the interest of users in the Web pages of the Web site. Each user's interest can be manifested by the sequence of each user access. After processing the Log in the Web site and identifying each user access transaction, the access paths of all the users can be clustered. This is called path clustering. Each cluster can then represent the similar access interest of the users in the cluster. Presented in this paper is a new clustering approach: K paths to partition the users' access according to the interest of the users. In this approach, according to the requirement of the clustering, the new method is defined to measure similarity and to get the center of a cluster. The experiment shows that this approach is successful.
Keywords:Web mining  clustering
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