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International Journal of Machine Learning and Cybernetics

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02-08-2018 | Original Article

L-fuzzy concept analysis for three-way decisions: basic definitions and fuzzy inference mechanisms

Authors: Xiaoli He, Ling Wei, Yanhong She

Published in: International Journal of Machine Learning and Cybernetics | Issue 11/2018

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Abstract

In this paper, the basic ideas underlying fuzzy logic are introduced into the study of three-way formal concept analysis. This leads naturally to the notion of L-fuzzy three-way concepts. The L-fuzzy three-way operators and their inverse are defined and their properties are given. Based on these operators, two types of L-fuzzy three-way concepts are defined and the corresponding three-way concept lattices are constructed. A possibility theory reading of L-fuzzy three-way concepts is also provided. Moreover, the corresponding fuzzy inference method is studied. Two coherent fuzzy inference methods, the lower approximate fuzzy inference and the upper approximate fuzzy inference, are proposed, respectively.

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Title: L-fuzzy concept analysis for three-way decisions: basic definitions and fuzzy inference mechanisms
Authors: Xiaoli He
Ling Wei
Yanhong She
Publication date: 02-08-2018
Publisher: Springer Berlin Heidelberg
Published in: International Journal of Machine Learning and Cybernetics / Issue 11/2018
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI: https://doi.org/10.1007/s13042-018-0857-y

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