Evaluation of web usage mining approaches for user's next request prediction
Mathias Géry, Hatem Haddad · 2003
Analysis of Web server logs is one of the important challenge to provide Web intelligent services.In this paper, we describe a framework for a recommender system that predicts the user's next requests based on their behaviour discovered from Web Logs data. We compare results from three usage mining approaches: association rules, sequential rules and generalised sequential rules. We use two selection rules criteria: highest confidence and last-subsequence. Experiments are performed on three collections of real usage data: one from an Intranet Web site and two from an Internet Web site.