Ontology Generation from Session Data for Web Personalization

With an increasing continuous growth of information in WWW it is very difficult for the users to access the interested web pages from the website. Because day by day the information in the web is growing in an increasing manner so without any help system the user may spend more time to get the interested information from the website. To overcome the above problem, in this paper we propose a Model which create a User Interested Page Ontology (UIPO), it will be created by assigning weights and ranking the user interest by count the number of occurrence of each item which was collected from the web logs within a session for all users. The main feature of this model is, it generates UIPO dynamically from that it personalize the interested pages to the web users in their next access The proposed model is very useful for understanding the behavior of the users and also improving the web site design too. The performance of the new model in a session is also discussed in this paper.