Web Site Auditing Using Web Access Log Data

DOIResolve DOI: http://doi.org/10.1109/CNSR.2009.24
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TypeArticle
Proceedings titleProceedings of the Seventh Annual Communications Networks and Services Research Conference(CNSR'09)2009
ConferenceThe Seventh Annual Communications Networks and Services Research Conference(CNSR'09), Moncton, New Brunswick, May 11-13, 2009
ISBN978-1-4244-4155-6
Pages94101; # of pages: 8
SubjectWeb Access Log; Web site auditing; Fuzzy Clustering; Artificial Fish Swarm Algorithm
AbstractThis 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.
Publication date
PublisherIEEE Computer Society
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC)
Peer reviewedYes
NPARC number15261132
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Record identifiera8c3b395-7c24-48ea-a13c-f38900875e48
Record created2010-06-10
Record modified2016-05-09
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