Web Site Auditing Using Web Access Log Data

Si He; Nabil Balecel; Habib Hamam; Yassine Bouslimani; IEEE

doi:10.1109/CNSR.2009.24

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Conference proceeding

Web Site Auditing Using Web Access Log Data

Si He, Nabil Balecel, Habib Hamam, Yassine Bouslimani and IEEE

2009 7TH ANNUAL COMMUNICATION NETWORKS AND SERVICES RESEARCH CONFERENCE, pp.94-101

01/01/2009

DOI: https://doi.org/10.1109/CNSR.2009.24

Abstract

Engineering

Engineering, Electrical & Electronic

Science & Technology

Technology

Telecommunications

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.

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Details

Title: Web Site Auditing Using Web Access Log Data
Creators - without role: Si He - Université de Moncton
Nabil Balecel - Inst. for Inf. Technol., Nat. Res. Council of Canada Moncton, Moncton, NB
Habib Hamam - Université de Moncton
Yassine Bouslimani - Université de Moncton
IEEE
Publication Details: 2009 7TH ANNUAL COMMUNICATION NETWORKS AND SERVICES RESEARCH CONFERENCE, pp.94-101
Publisher: IEEE
Number of pages: 2
Grant note: Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada (NSERC); CGIAR
Identifiers: 9932319308331
Academic Unit: University Ha'il
Language: English
Resource Type: Conference proceeding