DocumentCode
2899483
Title
Knowledge Reductions in Fuzzy Information Systems
Author
Huang, Bing ; Zhou, Xian-Zhong ; Jiang, Xiao-yao
Author_Institution
Sch. of Inf. Sci., Nanjing Audit Univ.
fYear
2006
fDate
13-16 Aug. 2006
Firstpage
4169
Lastpage
4172
Abstract
Knowledge reduction is one of important issues in rough sets theory. Based on rough set models and knowledge reduction definitions, researching on the corresponding reduction methods is primary approach in knowledge reductions. In symbolic information systems, knowledge reduction definitions and algorithms are in depth examined, in which researches are concentrated on discernibility matrix and functions, heuristic algorithms, incremental algorithms, etc. Information systems are named as fuzzy information systems in which all values are fuzzy. In fuzzy information systems, some basic rough set models are presented, which are called fuzzy-rough set methods. In this paper, definitions of knowledge reductions in fuzzy information systems are improved, that is, some new knowledge reductions are proposed
Keywords
fuzzy set theory; knowledge engineering; rough set theory; fuzzy information systems; fuzzy-rough set methods; knowledge reductions; Cybernetics; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Heuristic algorithms; Information analysis; Information science; Information systems; Knowledge engineering; Machine learning; Management information systems; Rough sets; Rough sets; fuzzy information system; knowledge reduction;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location
Dalian, China
Print_ISBN
1-4244-0061-9
Type
conf
DOI
10.1109/ICMLC.2006.258937
Filename
4028803
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