Modern Information Retrieval
Integrating Web Usage and Content Mining for More Effective Personalization
EC-WEB '00 Proceedings of the First International Conference on Electronic Commerce and Web Technologies
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
A hybrid system for concept-based web usage mining
International Journal of Hybrid Intelligent Systems
A large-scale hidden semi-Markov model for anomaly detection on user browsing behaviors
IEEE/ACM Transactions on Networking (TON)
Adaptive Web SitesA Knowledge Extraction from Web Data Approach
Proceedings of the 2008 conference on Adaptive Web Sites: A Knowledge Extraction from Web Data Approach
Mining personalization interest and navigation patterns on portal
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
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A web site is a semi structured collection of differentkinds of data, whose motivation is show relevant informationto visitor and by this way capture her/his attention.Understand the specifics preferences that define the visitorbehavior in a web site, is a complex task. An approximationis suppose that it depend the content, navigationsequence and time spent in each page visited. These variablescan be extracted from the web log files and the website itself, using web usage and content mining respectively.Combining the describe variables, a similarity measureamong visitor sessions is introduced and used in a clusteringalgorithm, which identifies groups of similar sessions,allowing the analysis of visitors behavior.In order to prove the methodology's effectiveness, it wasapplied in a certain web site, showing the benefits of thedescribed approach.