Tracing Significant Association Rules Using Critical Least Association Rules Model

Zailani, Abdullah and Tutut, Herawan and Mustafa, Mat Deris (2013) Tracing Significant Association Rules Using Critical Least Association Rules Model. International Journal of Innovative Computing and Applications, 5 (1). pp. 3-17. ISSN 1751-648X (Print); 1751-6498 (Online). (Published)

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Mining of least association rules from large databases has received a great attention in knowledge discovery. These rules are very useful especially in tracing the unexceptional events or situations. Until this moment, the ratio of studies in this area is still unbalanced as compared to mine frequent rules. The difficulties level of mining these rules as compared to frequent rules are different since it involves with the excessive in computational costs, rather complicated and entailed a dedicated measurement. Therefore, this paper proposed an efficient model called critical least association rule (CLAR) to mine the significant rules so called critical least association rules. Several experiments with real and UCI datasets has shown that the CLAR successfully in producing the critical least association rules, up to 1.5 times faster and less 96% complexity than benchmarked FP-growth algorithm.

Item Type: Article
Uncontrolled Keywords: least association rules, efficient, critical
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 01 Apr 2016 02:02
Last Modified: 14 Jul 2016 01:43
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