Identifying user sessions from web server logs with integer programming
Intelligent Data Analysis - Business Analytics and Intelligent Optimization
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Analysis of user behavior on the Web presupposes a reliable reconstruction of the users' navigational activities. The quality of reconstructed sessions affects the result of Web usage mining. This paper presents a new approach for interleaved server session from Web server logs using m-order Markov model combined with a competitive algorithm. The proposed approach has the ability to reconstruct interleaved sessions from server logs. 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.