Web Site Auditing Using Web Access Log Data

被引：0

作者：

He, Si ^{[1
]}

Balecel, Nabil ^{[2
]}

Hamam, Habib ^{[1
]}

Bouslimani, Yassine ^{[1
]}

机构：

[1] Univ Moncton, Dept Elect Engn, Moncton, NB E1A 3E9, Canada

[2] Natl Res Council Canada, Inst Informat Technol, Moncton, NB K1A 0R6, Canada

来源：

2009 7TH ANNUAL COMMUNICATION NETWORKS AND SERVICES RESEARCH CONFERENCE | 2009年

基金：

加拿大自然科学与工程研究理事会;

关键词：

Web Access Log; Web site auditing; Fuzzy Clustering; Artificial Fish Swarm Algorithm;

D O I：

10.1109/CNSR.2009.24

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：94 / +

页数：2

共 13 条

[1] Validity-guided (re)clustering with applications to image segmentation [J].

Bensaid, AM ;

Hall, LO ;

Bezdek, JC ;

Clarke, LP ;

Silbiger, ML ;

Arrington, JA ;

Murtagh, RF .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1996, 4 (02) :112-123

[2]

Bezdek J.C., 1981, PATTERN RECOGNITION

[3]

Danna E., 2001, Auditing websites using their user access patterns

[4]

Gao S., 2006, Swarm intelligence algorithms and applications

[5]

GEORGIOS P, EUROPEAN J OPERATION

[6]

Han J.M. Kamber., 2001, DATA MINING CONCEPT

[7]

KOHAVI R, MINING E COMMERCE DA

[8]

Li X.L., 2002, System Engineering Theory and Practice, V11, P32

[9]

Mena J., 1999, DATA MINING YOUR WEB

[10]

NASRAOUI O, 1999, 8 FUZZ SYST ASS WORL

← 1 2 →