Automatic Recommendation for Online Users Using Web Usage Mining

A real world challenging task of the web master of an organization is to match the needs of user and keeptheir attention in their web site. So, only option is to capture the intuition of the user and provide themwith the recommendation list. Most specifically, an online navigation behavior grows with each passingday, thus extracting information intelligently from it is a difficult issue. Web master should use web usagemining method to capture intuition. A WUM is designed to operate on web server logs which containuser’s navigation. Hence, recommendation system using WUM can be used to forecast the navigationpattern of user and recommend those to user in a form of recommendation list. In this paper, we proposea two tier architecture for capturing users intuition in the form of recommendation list containing pagesvisited by user and pages visited by other user’s having similar usage profile. The practicalimplementation of proposed architecture and algorithm shows that accuracy of user intuition capturing isimproved.