Evaluation of web usage mining approaches for user's next request prediction

Authors:
Mathias Géry;Hatem Haddad
Affiliations:
Technical Research Centre of Finland, Espoo, Finland;Technical Research Centre of Finland, Espoo, Finland
Venue:
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
Year:
2003

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Abstract

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.