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一种新的Web用户群体和URL聚类算法的研究 被引量：11

Research on a new clustering algorithm of Web user communities and Web site's URLs
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摘要 提出一个基于Web日志的Web用户群体和站点URL聚类算法.使用用户浏览行为描述和用户浏览时间离散化方法建立了Web站点的用户事务矩阵,并在此基础上对Web用户群体和站点URL进行聚类.由于在聚类过程中同时考虑了用户对URL的浏览时间和访问次数,使算法的精度和效率都大大提高.同时,该算法能较好地处理类间重叠问题,使算法具有较好的实用性.最后对算法的有效性和可伸缩性进行了研究. By using new methods which are based on Web user＇s browsing behavior characterization and user＇s viewing time discretization, a new clustering algorithm for Web user communities and Web site＇s URLs is proposed. Web user access matrixes are set up on the preparation of Web logs. By considering user＇s viewing time and number of hits to Web site＇s URLs simultaneously, the accuracy and efficiency of the clustering algorithm are increased. The improved algorithm could solve the problem of the partial overlap bewteen clusters, which makes the algorithm more practical. The effectiveness and the sealability of the algorithm are studied through the experiments.
作者 宋江春 沈钧毅
机构地区 西安交通大学电子与信息工程学院
出处 《控制与决策》 EI CSCD 北大核心 2007年第3期284-288,共5页 Control and Decision
基金 国家自然科学基金项目(60173058)
关键词 WEB使用挖掘 用户浏览模式 用户访问矩阵 用户事务聚类 站点URL聚类 Web usage mining User browsing pattern User access matrix User session clustering Web site URL clustering
分类号 TP391.11 [自动化与计算机技术—计算机应用技术]
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参考文献10

  • 1Srivastava J,Cooley R,Deshpande M,et al.Web usage mining:Discovery and applications of usage patterns from web data[J].SIGKDD Explorations.2000,1(2):12-23.
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  • 7苏中,马少平,杨强,张宏江.基于Web-Log Mining的Web文档聚类[J].软件学报,2002,13(1):99-104. 被引量：29
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二级参考文献6

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共引文献28

同被引文献104

引证文献11

二级引证文献15

控制与决策
2007年 第3期

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