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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Perkowitz, M., Etzioni, O.: Towards adaptive web sites: conceptual framework and case study. Artificial Intelligence 118(1-2), 245–275 (2000)
Zaiane, O., Xin, M., Han, J.: Discovering web access patterns and trends by applying OLAP and data mining technology on web logs. In: Proceedings on Advances in Digital Libraries Conference, Melbourne, Australia, pp. 144–158 (1998)
Agrawal, R., Srikant, R.: Mining sequential patterns. In: Proceedings of the 11th International Conference on Data Engineering, Taipei, Taiwan, pp. 3–14 (1995)
Chen, M.S., Park, J.S., Yu, P.S.: Efficient data mining for path traversal patterns. IEEE Transaction, Knowledge Data Engineering 10(2), 209–221 (1998)
Nasraoui, O., Petenes, C.: An intelligent web recommendation engine based on fuzzy approximate reasoning. In: IEEE International Conference on Fuzzy Systems, pp. 1116–1121 (2003)
Rohwer, J.A.: Least squares support vector machines for direction of arrival estimation. In: IEEE Antennas and Propagation Society, AP-S International Symposium (Digest), vol. 1, pp. 57–60 (2003)
Belkin, N.J., Croft, W.B.: Information filtering and information retrieval: two sides of the same coin. Communication of the ACM 35(12), 29–38 (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, J.J., Gao, J., Hu, J., Liao, B.S. (2004). Dynamic Mining for Web Navigation Patterns Based on Markov Model. In: Zhang, J., He, JH., Fu, Y. (eds) Computational and Information Science. CIS 2004. Lecture Notes in Computer Science, vol 3314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30497-5_125
Download citation
DOI: https://doi.org/10.1007/978-3-540-30497-5_125
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24127-0
Online ISBN: 978-3-540-30497-5
eBook Packages: Computer ScienceComputer Science (R0)