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结合Web站点结构的路径补充 被引量:2

Combining With the Structure of Website for Path Complement
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摘要 服务器端保存的Web访问日志含有大量的用户浏览信息,因此有效地利用该资源可以挖掘出有用的信息,并能得到用户个人的访问模式,从而为改善站点结构提供了支持。在结合站点拓扑结构的基础上,针对Web日志挖掘数据预处理过程中的路径补充提出了最短向后父节点算法(SBFN)。研究表明该算法能够对Web日志中的用户访问路径进行补充,从而为解决站点结构优化问题提供了方案。 Because the server preserves Web visited logs that contain a lot of user browsing information, so if people can make full use of the resource to mine useful information and acquire accessing patterns of single user, then it can provide support to improve the structure of Website. Based on the structure of Website proposes a new method called SBFN(shortcut backwards father node) ,aiming at the path complement in the data preprocessing of Web log mining. The study indicates that the arithmetic can complete the user browsing path in the Web log, so it provides a plan for the problem of improving structure of Website.
出处 《计算机技术与发展》 2007年第6期120-122,共3页 Computer Technology and Development
关键词 WEB日志 用户访问路径 网站结构 数据预处理 路径补充 Web log user browsing path structure of website data preprocessing path complement
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参考文献6

  • 1鲍钰,黄国兴,张召.基于Web日志挖掘的网站结构优化方法[J].计算机工程,2003,29(12):82-84. 被引量:12
  • 2Reichle M,Perner P,Klaus-Dieter A.Data Preparation of Web Log Files for Marketing Aspects Analyses[J].Lecture Notes in Computer Science,2006,4065:131 -145.
  • 3Baglioni M,Ferrara U,Romei A,et al.Preprocessing and Mining Web Log Data for Web Personalization[J].Lecture Notes in Computer Science,2003,2829:237-249.
  • 4Sun Liping,Zhang Xiuzhen.Efficient Frequent Pattern Mining on Web Logs[J].Lecture Notes in Computer Science,2004,3007:533-542.
  • 5吴强,梁继民,杨万海.Web日志挖掘预处理中的用户识别技术[J].计算机科学,2002,29(4):64-66. 被引量:21
  • 6Lei John Zhong,Ghorbani A.The Reconstruction of the Interleaved Sessions from a Server Log[J].Lecture Notes in Computer Science,2004,3060:133-145.

二级参考文献13

  • 1Shahabi C,ZarkeshA M,Abidi J,et al.Knowledge Discovery from Users Web-page Naviagtion.In Proc.of the 7th IEEE Intl.Workshop on Research Issues in Data Engineering (RIDE), 1997:20-29.
  • 2Pei J,Han J,Mortazavi-asl B,Zhu H.Mining Access Patterns Efficiently from Web Logs.In Proc.of the 4th Pacific-Asia Conf. on Knowledge Discovery and Data Mining, 2000-04:396-407.
  • 3Chen M S,Park J S,Yu P S.Data Mining for Path Traversal Patterns in a Web Environment.In Proc.of the 16th International Conference on Distributed Computing Systems, 1996-05:385-392.
  • 4Spiliopoulou M,Faulstich L C,Wilkler K.A Data Miner Analyzing the Navigational Behaviour of Web Users.In Proc.of the Workshop on Machine Learning in User Modelling of the ACAI99, Greece, 1999-07.
  • 5Leung Y, Leung K S. An Intelligent Expert Systems Shell for Knowledge~Based Geographic Information Systems. International Journal of Geographic Information Systems, 1993 (7): 351~ 355
  • 6Zaiane O R,Xin M,Han J. Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs. In: Proc. Advances in Digital Libraries Conf. (ADL'98),Santa Barbara,CA,April 1998. 19~29
  • 7Pei J,Han J,Mortazavi-Asl B,Zhu H. Mining Access Pattern efficiently from Web logs. In: Proc. 2000 Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD00), Kyoto,Japan,April 2000
  • 8Cooley R,Mobasher B,Srivastava J. Web mining: Information and Pattern discovery on the World Wide Web. In: Proc. IEEE Intl. Conf. Tools with AI,Dec. 1997
  • 9Pitow J. In Search of Reliable Usage Data on the WWW. In:Proc. of the 6th Intl. World Wide Web Conf. Santa Clara, CA,1997. 451~463
  • 10Cooley R,Mobasher B,Srivastava J. Grouping web page references into transactions for mining world web browsing patterns: [Technical Report TR 91-021]. University of Minnesota,Dept. of Computer Science ,Minneapolis, 1997

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