In this article, we integrate Relational Concept Analysis with fuzzy logic to explore multi-relational datasets including also vague information. Mainly, we aim to extract a family of fuzzy concept lattices from data organized as a collection of fuzzy formal contexts and fuzzy relations between objects of different types. To achieve this goal, we use existing fuzzy FCA techniques and fuzzy scaling quantifiers. Our principal contribution here consists of introducing and studying fuzzy scaling quantifiers, which are fuzzy quantifiers based on the concept of evaluative linguistic expression.
Boffa, S., Murinova, P., Novak, V. (2021). A proposal to extend Relational Concept Analysis with fuzzy scaling quantifiers [Formula presented]. KNOWLEDGE-BASED SYSTEMS, 231 [10.1016/j.knosys.2021.107452].
A proposal to extend Relational Concept Analysis with fuzzy scaling quantifiers [Formula presented]
Boffa S;
2021
Abstract
In this article, we integrate Relational Concept Analysis with fuzzy logic to explore multi-relational datasets including also vague information. Mainly, we aim to extract a family of fuzzy concept lattices from data organized as a collection of fuzzy formal contexts and fuzzy relations between objects of different types. To achieve this goal, we use existing fuzzy FCA techniques and fuzzy scaling quantifiers. Our principal contribution here consists of introducing and studying fuzzy scaling quantifiers, which are fuzzy quantifiers based on the concept of evaluative linguistic expression.File | Dimensione | Formato | |
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