Web Page Ranking by Markov Model and Generalized Hyperbolic Matrix

Project Discription

World Wide Web has necessitated the users to make use of automated tools to locate desired information resources and to follow and assess their usage pattern. Web page pre-fetching has been widely used to reduce the user access latency problem of the internet; its success mainly relies on the accuracy of web page prediction. Proposed model can be  mostly used for user navigation because of its high accuracy. It is a powerful method for arranging users’ session into clusters according to their similarity. This work develops the techniques to overcome the issues of web page prediction. Markov Modal has the most commonly used prediction model because of its high accuracy. However, research of the web page navigation is just at its beginning and much deeper understanding needs to be gained.

Whole work is divide into two steps first is the module builing this can be understand as the preparation of the model for the page re-ranking such as creating the system for the  web logs. After this step next step is to test the model where different surfers are pass in the model and it will predict the next page by the model.

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