首页    期刊浏览 2025年04月18日 星期五
登录注册

文章基本信息

  • 标题:Mining Frequent Closed Patterns using Sample-growth in Resource Effectiveness Data
  • 本地全文:下载
  • 作者:Zhang, Lihua ; Wang, Miao ; Zhai, Zhengjun
  • 期刊名称:Journal of Computers
  • 印刷版ISSN:1796-203X
  • 出版年度:2014
  • 卷号:9
  • 期号:5
  • 页码:1150-1158
  • DOI:10.4304/jcp.9.5.1150-1158
  • 语种:English
  • 出版社:Academy Publisher
  • 摘要:As the occurrence of failure of electronic resources is sudden, real-time record analysis on the effectiveness of all resources in the system can discover abnormal resources earlier and start using backup resources or restructure resources in time, thus managing abnormal situations and finally realizing health management of the system. This paper proposed an algorithm: MFPattern , for mining frequent closed resource patterns in resource effectiveness matrix. In order to improve the efficiency, MFPattern algorithm uses sample-growth method and effective pruning strategies to guarantee mining all frequent closed patterns without candidate maintenance. Different from the traditional frequent closed pattern, MFPattern algorithm can mine resource combination patterns with all resources very effective during work, those with simultaneous failure of resources and combination patterns in which some resources are very effective while some other resources have failure. The experimental result shows that our algorithm has more efficiently than existing algorithms.
  • 关键词:frequent pattern;closed;resource
国家哲学社会科学文献中心版权所有