Efficient Mining Maximal Variant and Low Usage Rate Biclusters without Candidate Maintenance in Real Function-Resource Matrix: The DeCluster Algorithm

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• 作者：Lihua Zhang (25) (26)
  Miao Wang (26)
  Zhengjun Zhai (25)
  Guoqing Wang (25) (26)
  
• 关键词：bicluster ; variant usage rate ; low usage rate ; function ; resource
• 刊名：Lecture Notes in Computer Science
• 出版年：2013
• 出版时间：2013
• 年：2013
• 卷：8347
• 期：1
• 页码：95-106
• 全文大小：357KB
• 作者单位：Lihua Zhang (25) (26)
  Miao Wang (26)
  Zhengjun Zhai (25)
  Guoqing Wang (25) (26)
  
  25. School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, China, 710072
  26. Science and Technology on Avionics Integration Laboratory, Shanghai, China, 200233
  
• ISSN：1611-3349

文摘

The health of the functional layer includes the status of functional components in the hierarchy range and overall health status of the whole functional layer. This paper proposed an efficient bicluster mining algorithm: DeCluster, to effectively mine all biclusters with maximal variant usage rate and maximal low usage rate in the real-valued function-resource matrix. First, a sample weighted graph is constructed, it includes all resource collections between both samples that meet the definition of variant usage rate or low usage rate; then, all biclusters with maximal variant usage rate and low usage rate meeting the definition are mined with the mining method of using depth-first sample-growth in the weight graph made. To improve the mining efficiency of the algorithm, DeCluster algorithm uses multiple pruning strategies to ensure the mining of maximal bicluster without candidate maintenance. The experimental result show our algorithm is efficiently than traditional algorithm.