Title: An efficient hierarchical clustering model for grouping web transactions

Authors: Darenna Syahida Suib, Mustafa Mat Deris

Addresses: Faculty of Information Technology and Multimedia, Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat, Johor. ' Faculty of Information Technology and Multimedia, Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat, Johor

Abstract: Clustering is one of the techniques used to obtain useful information from web log file for better understanding of customer behaviour. Two clustering techniques that commonly used are Greedy Hierarchical Item Set-Based Clustering (GHIC) algorithm and Hierarchical Clustering Algorithm (HCA). The algorithms, however, have its weaknesses in terms of processing times and time complexity. This paper proposes a new approach called Hierarchical Pattern-Based Clustering (HPBC) algorithm to improve the processing times based on the difference of mean support values of each cluster. The simulation revealed that the proposed algorithm outperformed the HCA and GHIC up to 100% and 50% respectively, with less time complexity.

Keywords: HPBC; hierarchical clustering; pattern based clustering; processing times; time complexity; web transactions; customer behaviour; web log files; blogs.

DOI: 10.1504/IJBIDM.2008.020516

International Journal of Business Intelligence and Data Mining, 2008 Vol.3 No.2, pp.147 - 157

Published online: 28 Sep 2008 *

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