A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Database techniques for the World-Wide Web: a survey
ACM SIGMOD Record
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
On Clustering Validation Techniques
Journal of Intelligent Information Systems
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
Data Mining for Intelligent Web Caching
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Low-complexity fuzzy relational clustering algorithms for Web mining
IEEE Transactions on Fuzzy Systems
Data preparation of web log files for marketing aspects analyses
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
A new dissimilarity measure for online social networks moderation
Web Intelligence and Agent Systems - Web Intelligence and Communities
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Various commercial and scientific applications require analysis of user behaviour in the Internet. For example, web marketing or network technical support can benefit from web users classification. This is achievable by tracking pages visited by the user during one session (one visit to the particular site). For automated user sessions classification we propose distance that compares sessions judging by the sequence of pages in them and by categories of these pages. Proposed distance is based on Levenshtein metric. Fuzzy C Medoids algorithm was used for clustering, since it has almost linear complexity. Davies-Bouldin, Entropy, and Bezdek validity indices were used to assess the qualities of proposed method. As testing shows, our distance outperforms in this domain both Euclidian and Edit distances.