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A Constraint Programming Approach for Web Log Mining

Author

Listed:
  • Amina Kemmar

    (LITIO, University of Oran 1, Ahmed Ben Bella, Oran, Algeria)

  • Yahia Lebbah

    (LITIO, University of Oran 1, Ahmed Ben Bella, Oran, Algeria)

  • Samir Loudni

    (GREYC (CNRS UMR 6072), University of Caen, Caen, France)

Abstract

Mining web access patterns consists in extracting knowledge from server log files. This problem is represented as a sequential pattern mining problem (SPM) which allows to extract patterns which are sequences of accesses that occur frequently in the web log file. There are in the literature many efficient algorithms to solve SMP (e.g., GSP, SPADE, PrefixSpan, WAP-tree, LAPIN, PLWAP). Despite the effectiveness of these methods, they do not allow to express and to handle new constraints defined on patterns, new implementations are required. Recently, many approaches based on constraint programming (CP) was proposed to solve SPM in a declarative and generic way. Since no CP-based approach was applied for mining web access patterns, the authors introduce in this paper an efficient CP-based approach for solving the web log mining problem. They bring back the problem of web log mining to SPM within a CP environment which enables to handle various constraints. Experimental results on non-trivial web log mining problems show the effectiveness of the authors' CP-based mining approach.

Suggested Citation

  • Amina Kemmar & Yahia Lebbah & Samir Loudni, 2016. "A Constraint Programming Approach for Web Log Mining," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 11(4), pages 24-42, October.
    • Handle: RePEc:igg:jitwe0:v:11:y:2016:i:4:p:24-42
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