Counting Formal Concepts of A Random Formal Context

It is well-known that counting formal concepts in a formal context is a challenging #P-complete problem. To determine the expected number of formal concepts in a formal context, we consider a random formal context, where each attribute occurs with a certain probability. Utilizing mathematical expectation, we derive both the lower and upper bounds for the superpolynomial representation of the expected number of formal concepts, with the upper bound in superpolynomial form being presented for the first time.

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Published
2024-09-20
DOI
https://doi.org/10.1109/icmlc63072.2024.10935090
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Counting Formal Concepts of A Random Formal Context

Jiaming Wu, Chengling Zhang, Lanzhen Yang, Eric C.C. Tsang
Semantic Web and Ontologies
article

Counting Formal Concepts of A Random Formal Context

Jiaming Wu, Chengling Zhang, Lanzhen Yang, Eric C.C. Tsang
article en

Abstract

It is well-known that counting formal concepts in a formal context is a challenging #P-complete problem. To determine the expected number of formal concepts in a formal context, we consider a random formal context, where each attribute occurs with a certain probability. Utilizing mathematical expectation, we derive both the lower and upper bounds for the superpolynomial representation of the expected number of formal concepts, with the upper bound in superpolynomial form being presented for the first time.

Macau University of Science and Technology (MO)
Fundo para o Desenvolvimento das Ciências e da Tecnologia
Reduced inequalities
Openalex Percentile: Top 74%
Semantic Web and Ontologies
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