Hybrid approach for predicting the behavior of Web users

Hybrid approach for predicting the behavior of Web users in this paper, we propose the design and implementation of a hybrid system by combining several data mining techniques to capture user\´s Web browsing behavior. User navigation sessions that represent the interaction with a given Website are used to construct hypertext probability grammar (HPG). The production with high probability in HPG represents the most favorable user browsing trail. The HPG results will be further used to construct N×M matrix, and a clustering algorithm are applied to extract clusters of behaviors. N-gram model is used based on the assumption that Website visitors have limited memory of what they visited before, and the choice of the next page to visit does not depend on all pages visited previously; but only the N -1 page. N-gram will not generate strong x where |x| \n\n\t\t