Mining Access Patterns Eeciently from Web Logs ?

نویسندگان

  • Jian Pei
  • Jiawei Han
  • Behzad Mortazavi-asl
  • Hua Zhu
چکیده

With the explosive growth of data available on the World Wide Web, discovery and analysis of useful information from the World Wide Web becomes a practical necessity. Web access pattern, which is the sequence of accesses pursued by users frequently, is a kind of interesting and useful knowledge in practice. In this paper, we study the problem of mining access patterns from Web logs e ciently. A novel data structure, called Web access pattern tree, or WAP-tree in short, is developed for e cient mining of access patterns from pieces of logs. The Web access pattern tree stores highly compressed, critical information for access pattern mining and facilitates the development of novel algorithms for mining access patterns in large set of log pieces. Our algorithm can nd access patterns from Web logs quite e ciently. The experimental and performance studies show that our method is in general an order of magnitude faster than conventional methods.

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تاریخ انتشار 2000