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  • 标题:Mining Closed Strong Association Rules by Rule-growth in Resource Effectiveness Matrix
  • 本地全文:下载
  • 作者:Zhang, Lihua ; Wang, Miao ; Zhai, Zhengjun
  • 期刊名称:Journal of Software
  • 印刷版ISSN:1796-217X
  • 出版年度:2014
  • 卷号:9
  • 期号:9
  • 页码:2417-2426
  • DOI:10.4304/jsw.9.9.2417-2426
  • 语种:English
  • 出版社:Academy Publisher
  • 摘要: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.
  • 关键词:frequent pattern;closed;resource
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