Identifying User Sessions from Web Server Logs with Integer Programming

摘要

Web usage mining has proven to be an important advance for e-businesssystems, both by finding web user buying patterns and suggesting ways to improveweb user navigation. A primary input for web usage mining is web user sessionsthat must be constructed from web server logs (called sessionization) when suchsessions are not otherwise identified. We use bipartite cardinality matching and amore general integer program to construct sessions. We also propose several variationsof our integer program to provide additional insights into session characteristics.For testing, we retrieve 15 months of web server logs and corresponding realsessions from an academic web site. We compare real sessions, results obtained byour optimization models, and results from a commonly-used timeout heuristic. Wefind our optimization models dominate the timeout heuristic using several comparisonmeasures. Solution time for a typical month is seven hours for our integer program,30 minutes for our bipartite cardinality matching, and about 1 minute for theheuristic. Although solution time is significantly greater for the integer program, itsvariations contribute additional analysis of web user behavior.