An efficient hierarchical clustering model for grouping web transactions

Authors:
Darenna Syahida Suib;Mustafa Mat Deris
Affiliations:
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
Venue:
International Journal of Business Intelligence and Data Mining
Year:
2008

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Abstract

Clustering is one of the techniques used to obtain usefulinformation from web log file for better understanding of customerbehaviour. Two clustering techniques that commonly used are GreedyHierarchical Item Set-Based Clustering (GHIC) algorithm andHierarchical Clustering Algorithm (HCA). The algorithms, however,have its weaknesses in terms of processing times and timecomplexity. This paper proposes a new approach called HierarchicalPattern-Based Clustering (HPBC) algorithm to improve the processingtimes based on the difference of mean support values of eachcluster. The simulation revealed that the proposed algorithmoutperformed the HCA and GHIC up to 100% and 50% respectively, withless time complexity.