Title :
Web Site Auditing Using Web Access Log Data
Author :
He, Si ; Balecel, Nabil ; Hamam, Habib ; Bouslimani, Yassine
Author_Institution :
Electr. Eng. Dept., Univ. de Moncton Moncton, Moncton, NB
Abstract :
This paper applies a method to use the access log data to audit Web sites. 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.
Keywords :
Web sites; artificial intelligence; auditing; information retrieval; optimisation; pattern clustering; Web access log data; Web site auditing; artificial fish swarm algorithm; fuzzy clustering algorithm; standard fuzzy C-means; Clustering algorithms; Communication networks; Companies; Councils; Data analysis; Helium; Information technology; Marine animals; Measurement standards; Web sites; Artificial Fish Swarm Algorithm; Fuzzy Clustering; Web Access Log; Web site auditing;
Conference_Titel :
Communication Networks and Services Research Conference, 2009. CNSR '09. Seventh Annual
Conference_Location :
Moncton, NB
Print_ISBN :
978-1-4244-4155-6
Electronic_ISBN :
978-0-7695-3649-1
DOI :
10.1109/CNSR.2009.24
