Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs

  • Authors:

  • Zhixiang Chen;Ada Wai-Chee Fu;Frank Chi-Hung Tong

  • Affiliations:

  • Department of Computer Science, University of Texas-Pan American, USA chen@cs.panam.edu;Department of Computer Science, Chinese University of Hong Kong, Hong Kong adafu@cse.cuhk.edu.hk;Department of Computer Science and Information Systems, The University of Hong Kong, Hong Kong ftong@eti.hku.hk

  • Venue:
  • World Wide Web
  • Year:
  • 2003

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Abstract

Although efficient identification of user access sessions from very large web logs is an unavoidable data preparation task for the success of higher level web log mining, little attention has been paid to algorithmic study of this problem. In this paper we consider two types of user access sessions, interval sessions and gap sessions. We design two efficient algorithms for finding respectively those two types of sessions with the help of some proposed structures. We present theoretical analysis of the algorithms and prove that both algorithms have optimal time complexity and certain error-tolerant properties as well. We conduct empirical performance analysis of the algorithms with web logs ranging from 100 megabytes to 500 megabytes. The empirical analysis shows that the algorithms just take several seconds more than the baseline time, i.e., the time needed for reading the web log once sequentially from disk to RAM, testing whether each user access record is valid or not, and writing each valid user access record back to disk. The empirical analysis also shows that our algorithms are substantially faster than the sorting based session finding algorithms. Finally, optimal algorithms for finding user access sessions from distributed web logs are also presented.