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