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
Link To Document :
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