Web Site Auditing Using Web Access Log Data

Abstract

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.