Clustering validity checking methods: part II
ACM SIGMOD Record
Web Usage Mining as a Tool for Personalization: A Survey
User Modeling and User-Adapted Interaction
LODAP: a log data preprocessor for mining web browsing patterns
AIKED'07 Proceedings of the 6th Conference on 6th WSEAS Int. Conf. on Artificial Intelligence, Knowledge Engineering and Data Bases - Volume 6
Clustering by competitive agglomeration
Pattern Recognition
Categorization of Web Users by Fuzzy Clustering
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
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Capturing the characteristics and preferences of Web users into user profiles is a fundamental task to perform in order to implement forms of personalization on a Web site. In this paper, we present a relational fuzzy clustering approach to extract significant user profiles from session data derived from log files. In particular, a modified version of the CARD clustering algorithm is proposed in order to produce well distinct clusters corresponding to profiles reflecting the actual user preferences embedded in the available session data. Experimental results on session data extracted from log files of a sample Web site are reported.