Proposed Approach For Web Page Access Prediction Using Populartiy And Similarity Based Page Rank Algorithm

Nowadays, the Web is an important source of information retrieval, and the users accessing the Web are from different backgrounds. The usage information about users are recorded in web logs. Analyzing web log files to extract useful patterns is called Web Usage Mining. Web usage mining approaches include clustering, association rule mining, sequential pattern mining etc. The web usage mining appr oaches can be applied to predict next page access. In this paper, we proposed a Page Rank-like algorithm is proposed for conducting web page access prediction. We extend the use of page rank algorithm for next page prediction with several navigational attributes, which are the similar ity of the page, size of the page, access-time of the page, duration of the page and transition(two pages visits sequentially) and frequency of page and transition.