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Factorizing formal contexts from closures of necessity operators

arXiv 2604.09582 ↗First posted 25 Feb 2026cs.AI cs.LOcited by 0

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Abstract (arXiv)

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~citedubois: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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 42 references that are in the map. First posted on arXiv 25 Feb 2026.

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References · 1

  1. 2013From-Below Approximations in Boolean Matrix Factorization: Geometry and New Algorithmcited by 3

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