Volume 9 Number 9 (Sep. 2014)
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JSW 2014 Vol.9(9): 2417-2426 ISSN: 1796-217X
doi: 10.4304/jsw.9.9.2417-2426

Mining Closed Strong Association Rules by Rule-growth in Resource Effectiveness Matrix

Lihua Zhang1, 2, Miao Wang2, 3, Zhengjun Zhai1, Guoqing Wang1, 2, 3
1School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, China, 710072
2Science and Technology on Avionics Integration Laboratory, Shanghai, China, 200233
3China National Aeronautical Radio Electronics Research Institute, Shanghai, China, 200233

Abstract—Association rules mining approach can find the relationship among items. Using association rules mining algorithm to mine resource fault, can reduce the number of wrong alarm resources to be replaced. This paper proposed an efficient association rules mining algorithm: CSRule, for mining closed strong association rules based on association rule merging strategies. CSRule algorithm adopts several pruning strategies to mine closed strong association rules without storing the candidate set. To improve the mining efficiency, CSRule algorithm adopts effective pruning strategies to mine closed strong association rules in real time, instead of secondary mining only through the definition. The experimental results show our algorithm is more efficient than traditional algorithm.

Index Terms—frequent pattern, closed, resource


Cite: Lihua Zhang, Miao Wang, Zhengjun Zhai, Guoqing Wang, "Mining Closed Strong Association Rules by Rule-growth in Resource Effectiveness Matrix," Journal of Software vol. 9, no. 9, pp. 2417-2426, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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