Discovering better navigation sequences for the session construction problem
Data & Knowledge Engineering
On web services workflow mining
BPM'05 Proceedings of the Third international conference on Business Process Management
Modeling web usage profiles of cloud services for utility cost analysis
Proceedings of the Winter Simulation Conference
Effective web log mining and online navigational pattern prediction
Knowledge-Based Systems
Identifying user sessions from web server logs with integer programming
Intelligent Data Analysis - Business Analytics and Intelligent Optimization
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Web usage mining plays an important role in the personalizationof Web services, adaptation of Web sites, andthe improvement of Web server performance. It applies datamining techniques to discover Web access patterns fromWeb usage data. In order to discover access patterns, Webusage data should be reconstructed into sessions with orwithout user identification. However, not all Web server logscontain complete information for constructing user sessions.One approach for solving such a problem is to usetime-oriented heuristics to reconstruct user sessions.This paper describes improved statistical-based time-orientedheuristics for the reconstruction of user sessionsfrom a server log. Comparative analysis are carried out usingtwo similarity measures. The performance results of theproposed improved heuristics are promising and in somecases show reasonable improvements.