Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (10): 18-27.doi: 10.11896/jsjkx.230600049

• Granular Computing & Knowledge Discovery • Previous Articles     Next Articles

Method of Updating Formal Concept Under Covering Multi-granularity

WANG Taibin1, LI Deyu1,2, ZHAI Yanhui1,2   

  1. 1 College of Computer Science and Technology,Shanxi University,Taiyuan 030006,China
    2 Key Laboratory of Computational Intelligence and Chinese Information Processing(Shanxi University),Taiyuan 030006,China
  • Received:2023-06-05 Revised:2023-07-28 Online:2023-10-10 Published:2023-10-10
  • About author:WANG Taibin,born in 1998,master.His main research interests include granular computing and multi-scale analysis.LI Deyu,born in 1965,Ph.D.His main research interests include data mining,artificial intelligence and multi-label learning.
  • Supported by:
    National Natural Science Foundation of China(61972238,62072294).

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Abstract: Multi-granularity formal concept analysis is an important tool for data mining and knowledge discovery.This paper studies the methods of coarsening and refining formal concepts under multi-granularity.Firstly,it is proved that the existing concept coarsening and updating algorithms will lead to concept deletion,and the concept coarsening algorithm is supplemented and improved by analyzing the characteristics of missing concepts.Secondly,it is proved that the existing concept refinement and updating algorithms will generate redundant concepts.The time complexity is high,so the existing concept refinement updating algorithm is optimized,and the performance advantages of the proposed concept refinement algorithm are verified by time complexity analysis and comparative experiments.

Key words: Granular computing, Formal concept analysis, Muti-granularity formal context, Covering muti-granularity, Updating concept

CLC Number: 

  • TP18
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