doi: 10.4304/jsw.9.9.2417-2426
Mining Closed Strong Association Rules by Rule-growth in Resource Effectiveness Matrix
- 1 School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, China, 710072
- 2 Science and Technology on Avionics Integration Laboratory, Shanghai, China, 200233
- 3 China 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: <em>CSRule</em>, for mining closed strong association rules based on association rule merging strategies. <em>CSRule</em> algorithm adopts several pruning strategies to mine closed strong association rules without storing the candidate set. To improve the mining efficiency, <em>CSRule</em> 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.
Keywords
- frequent pattern
- closed
- resource
How to Cite
Lihua Zhang, Miao Wang, Zhengjun Zhai, and 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. https://doi.org/ 10.4304/jsw.9.9.2417-2426
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).