DocumentCode :
2282946
Title :
Particle Swarm Optimization Based Clustering of Web Usage Data
Author :
Alam, Shafiq ; Dobbie, Gillian ; Riddle, Patricia
Author_Institution :
Dept. of Comput. Sci., Univ. of Auckland, Auckland
Volume :
3
fYear :
2008
fDate :
9-12 Dec. 2008
Firstpage :
451
Lastpage :
454
Abstract :
Web session clustering is one of the important Web usage mining techniques which aims to group usage sessions on the basis of some similarity measures. In this paper we describe a new Web session clustering algorithm that uses particle swarm optimization. We review the existing Web usage clustering techniques and propose a swarm intelligence based PSO-clustering algorithm for the clustering of Web user sessions. The proposed algorithm works independently without hybridization with any other clustering algorithm. The results show that our approach performs better than the benchmark k-means clustering algorithm for clustering Web usage sessions.
Keywords :
Internet; data mining; particle swarm optimisation; pattern clustering; Web session clustering; Web usage data clustering; Web usage mining; particle swarm optimization; similarity measure; swarm intelligence; Clustering algorithms; Communication system software; Computer science; Data mining; Insects; Intelligent agent; Particle measurements; Particle swarm optimization; Software algorithms; Web mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
Type :
conf
DOI :
10.1109/WIIAT.2008.292
Filename :
4740819
Link To Document :
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