A new distance metric on strings computable in linear time
Discrete Applied Mathematics
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A Space-Economical Suffix Tree Construction Algorithm
Journal of the ACM (JACM)
Linear Algorithm for Data Compression via String Matching
Journal of the ACM (JACM)
Automatic personalization based on Web usage mining
Communications of the ACM
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
Clustering web documents: a phrase-based method for grouping search engine results
Clustering web documents: a phrase-based method for grouping search engine results
Mining Navigation Patterns Using a Sequence Alignment Method
Knowledge and Information Systems
Discovering Social Networks from Event Logs
Computer Supported Cooperative Work
Linear pattern matching algorithms
SWAT '73 Proceedings of the 14th Annual Symposium on Switching and Automata Theory (swat 1973)
Identifying web navigation behaviour and patterns automatically from clickstream data
International Journal of Web Engineering and Technology
User Segmentation Based on Finding Communities with Similar Behavior on the Web Site
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
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Web site community analysis is one of the most valuable tools which can be used for user segmentation in web marketing sphere. The user segmentation is successfully used in campaign analysis, for web/product/service recommendation, or for web usage optimization. This type of analysis can be helpful in web performance analysis, web usability or accessibility as well. Various software is available for user behavior analysis or for analysis of user interaction with the web site. However, most of them have the user segmentation based only on statistical measurement of such information like click-through rates, identification of popular paths and others. In this paper there is presented the web site community analysis oriented to the user segmentation. The analysis is based on the users' similar behavior on the website. For the identification of similar behavioral patterns was proposed the algorithm based on sequential pattern mining method combined with clustering using generalized suffix tree data structure.