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Automatic detection of semantic primitives using optimization based on genetic algorithm
In this article, we propose a method for the automatic retrieval of a set of semantic primitive words from an explanatory dictionary and a novel evaluation procedure for the obtained set of primitives. The approach is based on the representation of the dictionary as a directed graph with a single-ob...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280668/ https://www.ncbi.nlm.nih.gov/pubmed/37346646 http://dx.doi.org/10.7717/peerj-cs.1282 |
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author | Kostiuk, Yevhen Pichardo-Lagunas, Obdulia Malandii, Anton Sidorov, Grigori |
author_facet | Kostiuk, Yevhen Pichardo-Lagunas, Obdulia Malandii, Anton Sidorov, Grigori |
author_sort | Kostiuk, Yevhen |
collection | PubMed |
description | In this article, we propose a method for the automatic retrieval of a set of semantic primitive words from an explanatory dictionary and a novel evaluation procedure for the obtained set of primitives. The approach is based on the representation of the dictionary as a directed graph with a single-objective constrained optimization problem via a genetic algorithm with the PageRank scoring model. The problem is defined as a subset selection. The algorithm is fit to search for the sets of words that should fulfil several requirements: the cardinality of the set should not exceed empirically selected limits and the PageRank word importance score is minimized with cycle prevention thresholding. In the experiments, we used the WordNet dictionary for English. The proposed method is an improvement over the previous state-of-the-art solutions. |
format | Online Article Text |
id | pubmed-10280668 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102806682023-06-21 Automatic detection of semantic primitives using optimization based on genetic algorithm Kostiuk, Yevhen Pichardo-Lagunas, Obdulia Malandii, Anton Sidorov, Grigori PeerJ Comput Sci Algorithms and Analysis of Algorithms In this article, we propose a method for the automatic retrieval of a set of semantic primitive words from an explanatory dictionary and a novel evaluation procedure for the obtained set of primitives. The approach is based on the representation of the dictionary as a directed graph with a single-objective constrained optimization problem via a genetic algorithm with the PageRank scoring model. The problem is defined as a subset selection. The algorithm is fit to search for the sets of words that should fulfil several requirements: the cardinality of the set should not exceed empirically selected limits and the PageRank word importance score is minimized with cycle prevention thresholding. In the experiments, we used the WordNet dictionary for English. The proposed method is an improvement over the previous state-of-the-art solutions. PeerJ Inc. 2023-04-05 /pmc/articles/PMC10280668/ /pubmed/37346646 http://dx.doi.org/10.7717/peerj-cs.1282 Text en ©2023 Kostiuk et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Algorithms and Analysis of Algorithms Kostiuk, Yevhen Pichardo-Lagunas, Obdulia Malandii, Anton Sidorov, Grigori Automatic detection of semantic primitives using optimization based on genetic algorithm |
title | Automatic detection of semantic primitives using optimization based on genetic algorithm |
title_full | Automatic detection of semantic primitives using optimization based on genetic algorithm |
title_fullStr | Automatic detection of semantic primitives using optimization based on genetic algorithm |
title_full_unstemmed | Automatic detection of semantic primitives using optimization based on genetic algorithm |
title_short | Automatic detection of semantic primitives using optimization based on genetic algorithm |
title_sort | automatic detection of semantic primitives using optimization based on genetic algorithm |
topic | Algorithms and Analysis of Algorithms |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280668/ https://www.ncbi.nlm.nih.gov/pubmed/37346646 http://dx.doi.org/10.7717/peerj-cs.1282 |
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