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Scalable model for mining critical least association rules

Abdullah, Zailani and Herawan, Tutut and Mat Deris, Mustafa (2010) Scalable model for mining critical least association rules. In: ICICA'10: Proceedings of the First International Conference on Information Computing and Applications, 15-18 October 2010, Tangshan, China.

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Abstract

A research in mining least association rules is still outstanding and thus requiring more attentions. Until now; only few algorithms and techniques are developed to mine the significant least association rules. In addition, mining such rules always suffered from the high computational costs, complicated and required dedicated measurement. Therefore, this paper proposed a scalable model called Critical Least Association Rule (CLAR) to discover the significant and critical least association rules. Experiments with a real and UCI datasets show that the CLAR can generate the critical least association rules, up to 1.5 times faster and less 100% complexity than benchmarked FP-Growth.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: least association rules; model; scalable
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 15 Nov 2015 08:16
Last Modified: 15 Nov 2015 08:16
URI: http://eprints.uthm.edu.my/id/eprint/3597
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