• DocumentCode
    2890023
  • Title

    Granularity of knowledge, indiscernibility and rough sets

  • Author

    Pawlak, Zdzislaw

  • Author_Institution
    Inst. of Theor. & Appl. Inf., Polish Acad. of Sci., Gliwice, Poland
  • Volume
    1
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    106
  • Abstract
    Granularity of knowledge has attracted attention of many researchers. This paper concerns this issue from the rough set perspective. Granularity is inherently connected with the foundation of rough set theory. The concept of the rough set hinges on classification of objects of interest into similarity classes, which form elementary building blocks (atoms, granules) of knowledge. These granules are employed to define basic concepts of the theory. In the paper basic concepts of rough set theory are defined and their granular structure pointed out. Next the consequences of granularity of knowledge for reasoning about imprecise concepts are discussed
  • Keywords
    inference mechanisms; set theory; uncertainty handling; imprecise concepts; indiscernibility; knowledge granularity; objects classification; reasoning; rough sets; Fasteners; Fuzzy sets; Informatics; Logic; Rough sets; Set theory; Size measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1098-7584
  • Print_ISBN
    0-7803-4863-X
  • Type

    conf

  • DOI
    10.1109/FUZZY.1998.687467
  • Filename
    687467