Using congruence relations to extract knowledge from concept lattices

Viaud, Jean-François; Bertet, Karell; Missaoui, Rokia; Demko, Christophe

doi:10.1016/j.dam.2016.11.021

Cited by 5 publications

(4 citation statements)

References 19 publications

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“…Reducing size of knowledge extracted from a formal context is also a recent issue in this research area because the size is sometime very large. The research in [12] reduced the size by congruent relations whereas in [13] by block relations. A research in [14] summarized this issue and classified all recent techniques in reducing the size of knowledge of concept lattice into 3: redundant information removal, simplification, and selection.…”

Section: Introductionmentioning

confidence: 96%

“…Another kind of background knowledge is from our prior knowledge. The kind of background knowledge exists and some researches used it for formal concept analysis [4,12,13,30,31,32,33]. Some of the researches used such background knowledge to remove or reject some extracted knowledges which are incompatible with it [4,30,31,32,33] where the extracted knowledge is in the form of attribute implications [4,30] and concepts [31,32,33].…”

Section: Introductionmentioning

confidence: 99%

“…Some of the researches used such background knowledge to remove or reject some extracted knowledges which are incompatible with it [4,30,31,32,33] where the extracted knowledge is in the form of attribute implications [4,30] and concepts [31,32,33]. The other researches used such background knowledge to reduce the size of extracted knowledge in the form of concept lattice [12,13].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Non-Redundant Implicational Base of Many-Valued Context Using SAT

Hidayat

Ahmad

Desa

2021

cai

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Some attribute implications in an implicational base of a derived context of many-valued context can be inferred from some other attribute implications together with its scales. The scales are interpretation of some values in the manyvalued context therefore they are a prior or an existing knowledge. In knowledge discovery, the such attribute implications are redundant and cannot be considered as new knowledge. Therefore the attribute implicational should be eliminated. This paper shows that the redundancy problem exists and formalizes a model to check the redundancy.

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Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Non-Redundant Implicational Base of Many-Valued Context Using SAT

Hidayat

Ahmad

Desa

2021

cai

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“…The prior knowledge is used as background knowledge in the process of formal concept analysis. Several studies used background knowledge to remove redundant knowledge which can be inferred from the background knowledge ( Hidayat, bin Ahmad & Ishak bin Desa, 2021 ; Krishnan & Cherukuri, 2019 ; Sumangali & Kumar, 2019 ; Stumme, 1996 ; Belohlávek & Vychodil, 2008a ; Viaud et al, 2016 ). An example of this study is to generate non-redundant implicational base ( Hidayat, bin Ahmad & Ishak bin Desa, 2021 ; Hidayat, 2005 ).…”

Section: Introductionmentioning

confidence: 99%

Non-redundant implicational base of formal context with constraints using SAT

Hidayat,

Ahmad,

Ngo

2024

PeerJ Computer Science

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An implicational base is knowledge extracted from a formal context. The implicational base of a formal context consists of attribute implications which are sound, complete, and non-redundant regarding to the formal context. Non-redundant means that each attribute implication in the implication base cannot be inferred from the others. However, sometimes some attribute implications in the implication base can be inferred from the others together with a prior knowledge. Regarding knowledge discovery, such attribute implications should be not considered as new knowledge and ignored from the implicational base. In other words, such attribute implications are redundant based on prior knowledge. One sort of prior knowledge is a set of constraints that restricts some attributes in data. In formal context, constraints restrict some attributes of objects in the formal context. This article proposes a method to generate non-redundant implication base of a formal context with some constraints which restricting the formal context. In this case, non-redundant implicational base means that the implicational base does not contain all attribute implications which can be inferred from the others together with information of the constraints. This article also proposes a formulation to check the redundant attribute implications and encoding the problem into satisfiability (SAT) problem such that the problem can be solved by SAT Solver, a software which can solve a SAT problem. After implementation, an experiment shows that the proposed method is able to check the redundant attribute implication and generates a non-redundant implicational base of formal context with constraints.

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