From user access patterns to dynamic hypertext linking
Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems
Analysis and design of server informative WWW-sites
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Personalization on the Net using Web mining: introduction
Communications of the ACM
Web usage mining for Web site evaluation
Communications of the ACM
Automatic personalization based on Web usage mining
Communications of the ACM
Towards adaptive Web sites: conceptual framework and case study
Artificial Intelligence - Special issue on Intelligent internet systems
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
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
A Granular Approach for Analyzing the Degree of Affability of a Web Site
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Yoda: An Accurate and Scalable Web-Based Recommendation System
CooplS '01 Proceedings of the 9th International Conference on Cooperative Information Systems
A Framework for Efficient and Anonymous Web Usage Mining Based on Client-Side Tracking
WEBKDD '01 Revised Papers from the Third International Workshop on Mining Web Log Data Across All Customers Touch Points
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Recent growth of startup companies in the area of Web Usage Mining is a strong indication of the effectiveness of this data in understanding user behaviors. However, the approach taken by industry towards Web Usage Mining is off-line and hence intrusive, static, and cannot differentiate between various roles a single user might play. Towards this end, several researchers studied probabilistic and distance-based models to summarize the collected data and maintain only the important features for analysis. The proposed models are either not flexible to trade-off accuracy for performance per application requirements, or not adaptable in real-time due to high complexity of updating the model. In this paper, we propose a new model, the FM model, which is flexible, tunable, adaptable, and can be used for both anonymous and on-line analysis. Also, we introduce a novel similarity measure for accurate comparison among FM models of navigation paths or cluster of paths. We conducted several experiments to evaluate and verify the FM model.