DocumentCode
538894
Title
Research of Attribute Reduction Algorithm about Knowledge System
Author
Lihua, Hu ; Shifei, Ding ; Hao, Ding ; Hu, Wang
Author_Institution
Sch. of Comput. Sci. & Technol., China Univ. of Min. & Technol., Xuzhou, China
Volume
2
fYear
2010
fDate
16-17 Dec. 2010
Firstpage
103
Lastpage
106
Abstract
Rough set (RS) theory is a mathematical tool to deal with vagueness and uncertainty effectively developed in recent years. It has been applied widely in data mining, artificial intelligence, decision support system, pattern recognition, etc. In RS theory, Attribute Reduction (AR) is one of the most important and key contents. Many scholars all over the world have made a considerable amount of research about it. This paper summarizes AR algorithms based on knowledge system, and lays stress on basic principles, existing problems and disadvantages about AR algorithms. The future direction and trends of AR research are discussed in the end.
Keywords
knowledge based systems; rough set theory; artificial intelligence; attribute reduction algorithm; data mining; decision support system; knowledge system; mathematical tool; pattern recognition; rough set theory; Algorithm design and analysis; Approximation algorithms; Approximation methods; Complexity theory; Data mining; Knowledge based systems; Lattices; attribute reduction (AR); discernibility matrix; knowledge system; positive region; rough set (RS);
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-9247-3
Type
conf
DOI
10.1109/GCIS.2010.241
Filename
5708797
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