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基于频繁访问页组的路径聚类研究 被引量：3

Research of path clustering based on frequently visited page groups
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摘要 基于用户会话的页面聚类算法旨在发现用户在浏览过程中频繁访问的页组,为站点管理员优化站点结构提供有力的依据。将介绍一种改进的基于频繁访问页组的路径聚类算法K-PathPlus,其中定义了新的兴趣度、内容链接因子。最后采用龙城热线网站日志进行真实测试,实验的结果是成功的。 The page clustering based on user sessions is to group the frequently visited pages,which can help the webmaster to optimize the site topology.This paper will introduce an improved clustering algorithm based on users＇ access interest. K-PathPlus defines new interest degree,content-link ratio.In the end a true experiment is done by using www.ty.sx.cn log file. The result of experiment is successful.
作者 吴俊杰 刘耀军 陈俊杰
机构地区 太原师范学院计算机系 太原理工大学计算机与软件学院
出处 《计算机工程与应用》 CSCD 北大核心 2010年第33期130-131,共2页 Computer Engineering and Applications
基金 山西省自然科学基金No.2008021025~~
关键词 访问兴趣 聚类 路径聚类 数据挖掘 兴趣度 内容链接因子 access interest clustering path clustering data mining interest degree content-link ratio
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献8

  • 1钱卫宁,周傲英.从多角度分析现有聚类算法(英文)[J].软件学报,2002,13(8):1382-1394. 被引量：86
  • 2吴俊杰,陈俊杰,赵栓柱.基于用户访问兴趣的路径聚类研究[J].计算机工程与应用,2005,41(36):170-171. 被引量：7
  • 3杨怡玲,管旭东,尤晋元.基于页面内容和站点结构的页面聚类挖掘算法[J].软件学报,2002,13(3):467-469. 被引量：20
  • 4Mobasher B,Dai H,Luo T,et al.Discovery and evaluation of aggregate usage profiles for Web personalization[J].Data Mining and Knowledge Discovery,2002,6(1):61-82.
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  • 8Tan P,Kumar V.Discovery of Web robot sessions based on their navigational patterns[J].Data Mining and Knowledge Discovery,2002,6(1):9-35.

二级参考文献42

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计算机工程与应用
2010年 第33期

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