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Evaluation of the prediction capability of a user behaviour mining approach for adaptive web sites

This article addresses the problem to predict user behaviours on a Web site which is very known to be an important way for improving the effectiveness of Web sites. Our objective is to evaluate our collaborative filtering approach of recommendation computation called the Broadway approach, according to the prediction feature. The main assumption of your approach is to take the sequence of user actions of a group into account for recommendation computation. For the prediction evaluation, we use the log files containing two months of usage from the site http://www.hyperreald.,org/music/machines/. We develop a prediction system based on our approach for that site and implement two others Web mining algorithms (statistics, Markov) in order to compare our work with them. This paper reports the main results issued from our different experiments.