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Incremental sequential pattern mining algorithms of Web site access in grid structure database
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  • 作者:Dawei Liu ; Saifeng Cai ; Xiaohong Guo
  • 关键词:Data mining ; Sequential pattern mining ; Web log ; Web access pattern ; Grid structure
  • 刊名:Neural Computing and Applications
  • 出版年:2017
  • 出版时间:March 2017
  • 年:2017
  • 卷:28
  • 期:3
  • 页码:575-583
  • 全文大小:
  • 刊物类别:Computer Science
  • 刊物主题:Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Probability and Statistics in Computer Science; Computational Science and Engineering; Image Processing and Computer Visi
  • 出版者:Springer London
  • ISSN:1433-3058
  • 卷排序:28
文摘
Sequential pattern mining is a process of knowledge discovery which finds the frequent subsequence as a mode from the sequence database. Web log database is typically dynamic. Web log records are generated constantly, and user access patterns will change accordingly. This study focused on taking advantage of the dynamic characteristics of the Web access database, delivering a fast and efficient incremental mining algorithm. An IncWTP algorithm suitable for Web access sequence mode is developed to handle non-simple path with dynamic data storage structure, and detect and delete the failed sequence data timely.

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