DocumentCode
444000
Title
On two types of generalized rough set approximations in incomplete information systems
Author
Wu, Wei-Zhi ; Xu, You-Hong
Author_Institution
Inf. Coll., Zhejiang Ocean Univ., China
Volume
1
fYear
2005
fDate
25-27 July 2005
Firstpage
303
Abstract
In this paper similarity relations and labeled block sets in incomplete information systems are introduced. Based on the two structures of granules, two rough set models are derived for mining of certain and possible rules in incomplete decision tables. The relationship between the two rough set models is examined.
Keywords
approximation theory; data mining; decision tables; information systems; rough set theory; generalized rough set approximation; granule structure; incomplete decision table; incomplete information system; labeled block set; rule mining; similarity relation; Computational Intelligence Society; Data mining; Educational institutions; Information systems; Intelligent systems; Knowledge acquisition; Oceans; Rough sets; Set theory; Rough sets; incomplete information systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2005 IEEE International Conference on
Print_ISBN
0-7803-9017-2
Type
conf
DOI
10.1109/GRC.2005.1547290
Filename
1547290
Link To Document