期刊文献+

一种WEB日志挖掘的数据预处理方法 被引量:3

Data Preprocessing Method for Web Usage Mining
下载PDF
导出
摘要 Web日志是目前Web数据挖掘的重要研究方向。数据预处理是Web日志挖掘中的关键技术。详细的介绍了Web日志挖掘的预处理过程。数据预处理包括数据清理、识别用户、识别会话和框架页面清理、路径补充。用户识别后,框架页面降低了数据挖掘的效率,可以通过过滤框架页面大幅度减少产生的无效页面数。 Web log mining is an important research direction about web mining.Data preprocessing is a key technology in web log mining.The article describes the preprocessing of mining logs in detail.Data preprocessing includes data clean,identifying user,recognizing session,cleaning up the frame of the page and supplementing path.After the user identification,the frame of the page reduces the efficiency of data mining.The number of invalid page can be significantly reduced through filtering the frame of page.
作者 符翔 金瓯
出处 《计算机系统应用》 2010年第8期204-207,共4页 Computer Systems & Applications
基金 国家科技攻关计划(2003ba104c)
关键词 WEB日志挖掘 数据预处理 框架页面 过滤 会话识别 web log mining data preprocess frame page filter recoginiton sessi
  • 相关文献

参考文献6

二级参考文献28

  • 1Levy A.Efficient Query Processing for Information - Gathering Agents[A].Proceedings of the Workshop on Intelligent Information Agents.Gaithersburg: MD.National Institute of Standards and Technology[ C],1994.
  • 2Hu X.Knowledge Discovery in Database: An Attribute - oriented Rough Set Approach [ D].University of Regina,Canada,1995.
  • 3杨炳儒.知识工程与知识发现[M].北京:冶金工业出版社,2001..
  • 4Anand S S, Patrick A R, Hughes J G. A data mining methodology for cross-sales. Knowledge Based Systems Journal, 1998,10(7):449~461
  • 5Park J S, Chen M S, Yu P S. Using A hash-based method with transaction trimming for mining association rules. IEEE Transactions on Knowledge and Data Eng., 1997, 9(5):813~825
  • 6Bfichner A G, Baumgarten M, Artand S S. Navigation pattern discovery from internet data. In: Proceedings of the 5th ACM International Conference on Knowledge Discovery and Data Mining (WEBKDD′99 Workshop) (SIGKDD′99), New York, 1999.25~30
  • 7Srikant R, Agrawal R. Mining generalized association rules. In: Proceedings of the 21st International Conference Very Large DataBase, Switzerland, 1995. 407~419
  • 8Srikant R, Agrawal R. Mining quantitative association rules in large relational tables. In: Proceedings of the ACM SIGMOD, Canada, 1996.1~12
  • 9Yang D L, Yang S H, Hong M C. An efficient web mining for session path patterns. In: Proceedings of International Computer Symposium 2000, Workshop on Software Eng. and Database Systems, Taiwan, 2000. 107~113
  • 10Brin S, Motwani R, Silverstein C. Beyond market baskets: Generalizing association rules to correlations. In: Proceedings of the ACM SIGMOD, Canada, 1996.255~276

共引文献144

同被引文献21

引证文献3

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部