Abstract
Session reconstruction is an essential step in Web usage mining. The quality of reconstructed sessions affects the result of Web usage mining. This paper presents a new approach of reconstructing sessions from Web server logs using the Markov chain model combined with a competitive algorithm. The proposed approach has the ability to reconstruct interleaved sessions from server logs. It is robust even if the client IP is not available in the log file. This capability makes our work distinct from other session reconstruction methods. The experiments show that our approach provides a significant improvement in regarding interleaved sessions compared to the traditional methods.
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Lei, J.Z., Ghorbani, A. (2004). The Reconstruction of the Interleaved Sessions from a Server Log. In: Tawfik, A.Y., Goodwin, S.D. (eds) Advances in Artificial Intelligence. Canadian AI 2004. Lecture Notes in Computer Science(), vol 3060. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24840-8_10
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DOI: https://doi.org/10.1007/978-3-540-24840-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22004-6
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