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Book Chapter
An Evolutionary Approach for Clustering User Access Patterns from Web Logs
Book Series
Lecture Notes in Computer Science
Publisher
Springer Berlin / Heidelberg
ISSN
0302-9743 (Print) 1611-3349 (Online)
Volume
Volume 4304/2006
Book
AI 2006: Advances in Artificial Intelligence
DOI
10.1007/11941439
Copyright
2006
ISBN
978-3-540-49787-5
Category
PART II: Regular Papers (5–7 Pages)
DOI
10.1007/11941439_145
Pages
1184-1188
Subject Collection
Computer Science
SpringerLink Date
Saturday, November 18, 2006
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PART II: Regular Papers (5–7 Pages)
An Evolutionary Approach for Clustering User Access Patterns from Web Logs
Rui Wu
1
(1)
School of Mathematics and Computer Science, Shanxi Normal University, Shanxi, 041004, China
Abstract
In this paper rough
c
-means is applied to cluster user access patterns, in which PSO(Particle Swarm Optimization) algorithm is employed to tune the threshold and relative importance of upper and lower approximations. The Davies-Bouldin clustering validity index is used as the fitness function that is minimized while arriving at an optimal clustering. The effectiveness of the algorithm is demonstrated by an experiment.
Keywords:
web clustering, fuzzy variable, rough set, web user access pattern, PSO.
Rui
Wu
Email:
wurui1971@eyou.com
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