Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Towards adaptive Web sites: conceptual framework and case study
Artificial Intelligence - Special issue on Intelligent internet systems
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs
ADL '98 Proceedings of the Advances in Digital Libraries Conference
Hi-index | 0.00 |
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.