Visualization of navigation patterns on a Web site using model-based clustering
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Knowledge discovery from users Web-page navigation
RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
Dynamic web log session identification with statistical language models
Journal of the American Society for Information Science and Technology - Special issue: Webometrics
Assessing users' interactions for clustering web documents: a pragmatic approach
Proceedings of the 21st ACM conference on Hypertext and hypermedia
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The problem of modeling and predicting a Web surfer's browsing patterns has gained increasing attention in recent years. In this paper we present our experience in clustering Web surfers using a mixture of Markov models with a real application of Livelink log data. We propose different techniques to improve the clustering performance, and evaluate the techniques through experiments.