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Attribute Classification and Reduct Computation in Multi-Adjoint Concept Lattices

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URI: http://hdl.handle.net/10498/30939

DOI: 10.1109/TFUZZ.2020.2969114

ISSN: 1063-6706

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reductos-algoritmo_referencias_Para_publicar.pdf (371.3Kb)
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Author/s
Antoni, Lubomir; Cornejo Piñero, María EugeniaAuthority UCA; Medina Moreno, JesúsAuthority UCA; Ramírez Poussa, EloísaAuthority UCA
Date
2021
Department
Matemáticas
Source
IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 29, NO. 5, pp. 1121-1132
Abstract
The problem of reducing information in databases is an important topic in formal concept analysis, which has been studied in several articles. In this article, we consider the fuzzy en- vironment of the multi-adjoint concept lattices, since it is a general fuzzy framework that allows us to easily establish degrees of pref- erence on the elements of the considered database. We introduce algorithms to discover the information contained in the relational system. By means of these algorithms, we classify the attributes of a multi-adjoint context, and build a minimal subset of attributes preserving the information of the original knowledge system.
Subjects
Concept lattice reduction; formal concept analysis; fuzzy sets
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
This work is under a Creative Commons License Attribution-NonCommercial-NoDerivatives 4.0 Internacional

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