A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Web user clustering from access log using belief function
Proceedings of the 1st international conference on Knowledge capture
Mining e-commerce data: the good, the bad, and the ugly
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining Your Website
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Validity-guided (re)clustering with applications to image segmentation
IEEE Transactions on Fuzzy Systems
Hi-index | 0.00 |
This paper applies a method to use the access log data to audit websites. It studies website auditing by (1) proposing a new fuzzy clustering algorithm that combines standard Fuzzy C-Means and the Artificial Fish Swarm Algorithm; (2) presenting a new measurement index for similarities between user sessions; and (3) providing an experiment on the execution of this new method. The results are encouraging and show the potential of our fuzzy clustering approach to assist in auditing web site.