Factorizing formal contexts from closures of necessity operators
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arXiv:2604.09582v1 Announce Type: new Abstract: Factorizing datasets is an interesting process in a multitude of approaches, but many times it is not possible or efficient the computation of a factorization of the dataset. A method to obtain independent subcontexts of a formal context with Boolean data was proposed in~\cite{dubois:2012}, based on the operators used in possibility theory. In this paper, we will analyze this method and study different properties related to the pairs of sets from w
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Computer Science > Artificial Intelligence
[Submitted on 25 Feb 2026]
Factorizing formal contexts from closures of necessity operators
Roberto G. Aragón, Jesús Medina, Eloísa Ramírez-Poussa
Factorizing datasets is an interesting process in a multitude of approaches, but many times it is not possible or efficient the computation of a factorization of the dataset. A method to obtain independent subcontexts of a formal context with Boolean data was proposed in~\cite{dubois:2012}, based on the operators used in possibility theory. In this paper, we will analyze this method and study different properties related to the pairs of sets from which a factorization of a formal context arises. We also inspect how the properties given in the classical case can be extended to the fuzzy framework, which is essential to obtain a mechanism that allows the computation of independent subcontexts of a fuzzy context.
Subjects: Artificial Intelligence (cs.AI); Logic in Computer Science (cs.LO)
Cite as: arXiv:2604.09582 [cs.AI]
(or arXiv:2604.09582v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2604.09582
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Journal reference: Comp. Appl. Math. 43, 124 (2024)
Related DOI:
https://doi.org/10.1007/s40314-024-02590-0
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Submission history
From: Roberto G. Aragón [view email]
[v1] Wed, 25 Feb 2026 19:32:09 UTC (400 KB)
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