Research Papers
An Association Rule Mining Algorithm Based on a Boolean Matrix
Authors:
Hanbing Liu ,
Department of Information & Electrical Engineering, Hebei University of Engineering, 056038 Handan Hebei, China
Baisheng Wang
Department of Information & Electric Engineering, Hebei University of Engineering, 056038 Handan Hebei, China
Abstract
Association rule mining is a very important research topic in the field of data mining. Discovering frequent itemsets is the key process in association rule mining. Traditional association rule algorithms adopt an iterative method to discovery, which requires very large calculations and a complicated transaction process. Because of this, a new association rule algorithm called ABBM is proposed in this paper. This new algorithm adopts a Boolean vector "relational calculus" method to discovering frequent itemsets. Experimental results show that this algorithm can quickly discover frequent itemsets and effectively mine potential association rules.
How to Cite:
Liu, H. & Wang, B., (2007). An Association Rule Mining Algorithm Based on a Boolean Matrix. Data Science Journal. 6, pp.S559–S565. DOI: http://doi.org/10.2481/dsj.6.S559
Published on 20 Sep 2007.
Peer Reviewed
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