From user access patterns to dynamic hypertext linking
Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems
Self-organizing maps
ACM Computing Surveys (CSUR)
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
Clustering Algorithms
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
Incremental Clustering for Mining in a Data Warehousing Environment
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
A Generalization-Based Approach to Clustering of Web Usage Sessions
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Web page clustering using a self-organizing map of user navigation patterns
Decision Support Systems - Special issue: Web 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
Model-Based Clustering and Visualization of Navigation Patterns on a Web Site
Data Mining and Knowledge Discovery
Profiling Web Usage in the Workplace: A Behavior-Based Artificial Intelligence Approach
Journal of Management Information Systems
Data & Knowledge Engineering
Visualization of multi-algorithm clustering for better economic decisions - The case of car pricing
Decision Support Systems
Profiling Retail Web Site Functionalities and Conversion Rates: A Cluster Analysis
International Journal of Electronic Commerce
Towards supporting expert evaluation of clustering results using a data mining process model
Information Sciences: an International Journal
Electronic Commerce Research and Applications
Customer grouping for better resources allocation using GA based clustering technique
Expert Systems with Applications: An International Journal
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This study introduces a simple but effective visualization system that allows decision makers to easily identify groups of visitors with different sequential navigation patterns. In particular, navigation sequences of visitors are encoded as an order-dependent format so that early visited pages have more weights in the clustering process. Experimental results on a real-world dataset show that Markov state-transition diagrams with transition probabilities based on the proposed scheme can be very useful for developing Web marketing programs tailored to visitors' preferences and interests.