Dynamic mining of users interest navigation patterns using naive Bayesian method

With the rapid growth of World Wide Web and e-commerce the study of users´ navigation patterns has become more important. Predicting users´ navigation behavior is an interesting issue for e-commerce enterprises. Web usage mining techniques can be used for modeling and predicting users´ navigation patterns. In fact, mining users´ navigation pattern is the fundamental approach for generating recommendations. In practice, the user interests are changeable, and it is difficult to track the exact user navigation pattern. In this paper we proposed an approach based on naïve Bayesian method for modeling and predicting users´ navigation behavior. We used Web server logs as source data, for Web usage mining.