Dynamic mining for web navigation patterns based on markov model

Abstract

Web user patterns can be used to create a more robust web information service in personalization. But the user interests are changeable, that is, they differ from one user to another, and they are constantly changing for a specific user. This paper presents a dynamic mining approach based on Markov model to solve this problem. Markov model is introduced to keep track of the changes of user interest according to his or her navigational behaviors. Some new concepts in the model are defined. An algorithm based on the model is then designed to learn the user's favorite navigation paths. The approach is implemented in an example website, and the experimental results proved the effective of our approach. © Springer-Verlag 2004.