An efficient hierarchical clustering model for grouping web transactions

Suib, Darenna Syahida and Mat Deris, Mustafa (2008) An efficient hierarchical clustering model for grouping web transactions. International Journal of Business Intelligence and Data Mining, 3 (2). pp. 147-157. ISSN 1743-8187 (Unpublished)

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Official URL: http://dx.doi.org/10.1504/IJBIDM.2008.020516

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.

Item Type:Article
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:Faculty of Computer Science and Information Technology > Department of Software Engineering
ID Code:3806
Deposited By:Normajihan Abd. Rahman
Deposited On:07 Aug 2017 17:38
Last Modified:07 Aug 2017 17:38

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