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
Link To Document :
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