DocumentCode
1659931
Title
Extension of rough set under incomplete information systems
Author
Wang, Guoyin
Author_Institution
Inst. of Comput. Sci. & Technol., Chongqing Univ. of Posts & Telecommun., China
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1098
Lastpage
1103
Abstract
The classical rough set theory is based on complete information systems. It classifies objects using upper-approximation and lower-approximation defined on an indiscernibility relation that is a kind of equivalent relation. In order to process incomplete information systems, the classical rough set theory needs to be extended, especially, the indiscernibility relation needs to be extended to some inequivalent relation. There are several extensions for the indiscernibility relation at present, such as tolerance relation, non-symmetric similarity relation, and valued tolerance relation. Unfortunately, these extensions have their own limitation. We develop a new extension of rough set theory that is based on a limited tolerance relation
Keywords
information systems; knowledge acquisition; probability; rough set theory; incomplete information systems; indiscernibility relation; limited tolerance relation; rough set theory; Computer science; Educational programs; Information systems; Knowledge acquisition; Probability; Set theory; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location
Honolulu, HI
Print_ISBN
0-7803-7280-8
Type
conf
DOI
10.1109/FUZZ.2002.1006657
Filename
1006657
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