Web log data clustering for a multi-agent recommendation system

In this paper, we propose an automatic way of recommending information to be visualized by users. The list of information to be recommended is generated based on the web logs of the users stored by the system in a multi relational database. This system is a web-based multi-agent system which provides geographical information and monitors the actions of the users by generating logs. Frequently, the system joins the relational web log data and runs a clustering algorithm in order to recommend a list of most accessed information up to that moment to registered users who log in the system.