Studies of Knowledge Reductions Based on Bayesian Rough Set Model

Author

Zhong, Jiaming ; Li, Dingfang

Author_Institution

Network Center, XiangNan Univ., Chenzhou

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

86

Lastpage

89

Abstract

Aiming at Bayesian rough set model, some new concepts of knowledge reduction are denoted such as the upper approximation reduction and the lower approximation reduction, the upper approximation discernible matrix and the lower approximation discernible matrix, the judgment theorems with respect to those reductions are obtained, from which we provide new approaches to knowledge reductions in information systems.

Keywords

Bayes methods; approximation theory; data mining; data reduction; information systems; matrix algebra; rough set theory; Bayesian rough set model; information system; judgment theorem; knowledge reduction; lower approximation discernible matrix; lower approximation reduction; upper approximation discernible matrix; upper approximation reduction; Artificial intelligence; Bayesian methods; Data mining; Fuzzy sets; Information systems; Information technology; Intelligent networks; Mathematical model; Mathematics; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3505-0

Type

conf

DOI

10.1109/IITA.Workshops.2008.221

Filename

4731887