Parallel Reducts Based on Attribute Significance

  • Dayong Deng
  • Dianxun Yan
  • Jiyi Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6401)


In the paper, we focus on how to get parallel reducts. We present a new method based on matrix of attribute significance, by which we can get parallel reduct as well as dynamic reduct. We prove the validity of our method in theory. The time complex of our method is polynomial. Experiments show that our method has advantages of dynamic reducts.


Rough Sets Attribute Significance Matrix Parallel Reducts Dynamic Reducts 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Dayong Deng
    • 1
    • 2
  • Dianxun Yan
    • 2
  • Jiyi Wang
    • 2
  1. 1.Xingzhi CollegeZhejiang Normal UniversityJinhuaChina
  2. 2.College of Mathematics, Physics and Information EngineeringZhejiang Normal UniversityJinhuaChina

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