Improved web page recommender system based on web usage mining

Web now becomes the backbone of the information. Today the major concerns are not the availability of information but rather obtaining the right information. Mining the web aims at discovering the hidden and useful knowledge from web hyperlinks, contents or usage logs. This paper focuses on improving the prediction of the next visited web pages and recommends them to the current anonymous user by assigning him to the best navigation profiles obtained by previous navigations of similar interested users. To represent the anonymous user’s navigation history, we used a window sliding method with size n over his current navigation session. Using CTI dataset the experimental results show higher prediction accuracy for the next visited pages for anonymous users compared to previous recommendation system