Dynamic mining of users interest navigation patterns using naive Bayesian method

Authors:
Mahdi Khosravi;Mohammad J. Tarokh
Affiliations:
Industrial Engineering Faculty, IT Engineering Group, K.N.Toosi University of Technology, Tehran, Iran;Industrial Engineering Faculty, IT Engineering Group, K.N.Toosi University of Technology, Tehran, Iran
Venue:
ICCP '10 Proceedings of the Proceedings of the 2010 IEEE 6th International Conference on Intelligent Computer Communication and Processing
Year:
2010

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Abstract

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 na茂ve Bayesian method for modeling and predicting users' navigation behavior. We used Web server logs as source data, for Web usage mining.