DocumentCode :
475921
Title :
Generalized attribute reduction in consistent decision formal context
Author :
Wang, Hong ; Zhang, Wen-xiu
Author_Institution :
Fac. of Sci., Zhongyuan Univ. of Technol., Zhengzhou
Volume :
1
fYear :
2008
fDate :
12-15 July 2008
Firstpage :
251
Lastpage :
256
Abstract :
Formal concept analysis, as an effective tool for knowledge discovery, has been successfully applied to various fields. This paper deals with approaches to generalized attribute reduction in consistent decision formal context. The concept of generalized attribute reduction in consistent decision formal context is first introduced. The judgement theorems and discernibility matrices are established, from which we provide the approaches to generalized attribute reduction in consistent decision formal context based on concept lattice.
Keywords :
data mining; decision theory; set theory; decision formal context; discernibility matrices; formal concept analysis; generalized attribute reduction; knowledge discovery; Artificial intelligence; Cybernetics; Data analysis; Information analysis; Lattices; Machine learning; Set theory; Attribute reduction; Concept lattice; Consistent set; Formal context;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4620413
Filename :
4620413
Link To Document :
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