Computing triadic generators and association rules from triadic contexts

Missaoui, Rokia; Ruas, Pedro H. B.; Kwuida, Léonard; Song, Mark A. J.; Ibrahim, Mohamed Hamza

doi:10.1007/s10472-022-09784-4

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…Por meio da Análise Formal de Conceitos (Missaoui et al, 2022) A regra número 1 apresenta os atributos peso, gestação e consultas médicas. O atributo peso entre 3000 e 3999 gramas aponta o peso ideal para evitar a mortalidade, a regra número 1 aponta também que a gestação de 37 a 41 semanas que é considerada parto normal e o atributo número de consultas 7 implicam em maior chance de sobrevivência.…”

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Applying formal concept analysis to characterize infant mortality

Song,

Galvez,

Santos

2024

CLIUM

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Infant mortality is characterized by the death of children under one year of age, a problem that affects a large part of the world’s population. In this context, we applied Formal Concept Analysis (FCA), a mathematical technique used in data analysis, to characterize infant mortality in two regions of the state of Minas Gerais: Belo Horizonte and Vale do Jequitinhonha. The aim is to describe infant mortality through data sets from the SIM and SINASC repositories. With FCA, concepts and rules that determine the main factors that contribute to infant mortality were extracted. Three scenarios were created for analysis. The first pointing out that weight, gestation, and APGAR are determinants for the child’s survival. In the second neonatal periods were used indicating that mortality, in the scenario where the child is born with low weight and early gestation, is higher than in the post-neonatal period. The third scenario was analyzed based on the International Classification of Diseases (ICD) indicating factors for mortality such as conditions and malformations in the post-neonatal period. The results reveal associations between different variables, allowing the profile of infant mortality to be traced in each region.

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Applying formal concept analysis to characterize infant mortality

Song,

Galvez,

Santos

2024

CLIUM

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“…As such data are also understudied in data mining in general, this is a unique occasion to position FCA and its extensions as a leading formalism. Some work has already been done in this direction in the field of multidimensional association rule mining [9,10].…”

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Some Notes on Polyadic Concept Analysis

Bazin¹,

Kahn²,

Noûs³

2022

Preprint

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Despite the popularity of Formal Concept Analysis (FCA) as a mathematical framework for data analysis, some of its extensions are still considered arcane. Polyadic Concept Analysis (PCA) is one of the most promising yet understudied of these extensions. This formalism offers many interesting open questions but is hindered in its dissemination by complex notations and a lack of agreed-upon basic definitions. In this paper, we discuss in a mostly informal way the fundamental differences between FCA and PCA in the relation between contexts, conceptual structures, and rules. We identify open questions, present partial results on the maximal size of concept n-lattices and suggest new research directions.

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Computing triadic generators and association rules from triadic contexts

Cited by 2 publications

References 14 publications

Applying formal concept analysis to characterize infant mortality

Applying formal concept analysis to characterize infant mortality

Some Notes on Polyadic Concept Analysis

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