A community detection algorithm for Web Usage Mining systems

Extracting knowledge from Web user's access data in Web Usage Mining (WUM) process is challenging task that is continuing to gain importance as the size of the web and its user-base increase. That's why meaningful methods have been proposed in the literature in order to understand the behaviour of the user in the web and improve the access modes to information. In this present work, we propose to emerge the community detection technique in WUM process, so we propose an approach of data extraction based on the modularity function. The obtained results illustrate the aptitude of the proposed algorithm to determine the optimal solution and to improve the Web design.