Studying Three Abstract Artists Based on a Multiplex Network Knowledge Representation

Discovering the influences between paintings and artists is very important for automatic art analysis. Lately, this problem has gained more importance since research studies are looking into explanations about the origin and evolution of artistic styles, which is a related problem. This paper propos...

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Main Authors: Luis Fernando Gutiérrez, Roberto Zarama, Juan Alejandro Valdivia
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2021/8506571
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spelling doaj-f9c740d182554b7ca33ca461fa3250d02021-04-19T00:04:22ZengHindawi-WileyComplexity1099-05262021-01-01202110.1155/2021/8506571Studying Three Abstract Artists Based on a Multiplex Network Knowledge RepresentationLuis Fernando Gutiérrez0Roberto Zarama1Juan Alejandro Valdivia2Departamento de Ingeniería IndustrialDepartamento de Ingeniería IndustrialDepartamento de FísicaDiscovering the influences between paintings and artists is very important for automatic art analysis. Lately, this problem has gained more importance since research studies are looking into explanations about the origin and evolution of artistic styles, which is a related problem. This paper proposes to build a multiplex artwork representation based on artistic formal concepts to gain more understanding about the aforementioned problem. We complement and built our approach on the previous notion of Creativity Implication Network. We used the recently proposed MultiRank algorithm to suggest possible explanations of the dynamic of some artistic styles. Our results corroborate some well-known facts about the artists analyzed and give qualitative and quantitative information that show the possibilities and strengths of the proposed framework. We plan to expand our analysis to include more abstract artworks. Ideally, we are going to be able to validate more our results and test how our methodology could be used to generate visual artifacts too.http://dx.doi.org/10.1155/2021/8506571
collection DOAJ
language English
format Article
sources DOAJ
author Luis Fernando Gutiérrez
Roberto Zarama
Juan Alejandro Valdivia
spellingShingle Luis Fernando Gutiérrez
Roberto Zarama
Juan Alejandro Valdivia
Studying Three Abstract Artists Based on a Multiplex Network Knowledge Representation
Complexity
author_facet Luis Fernando Gutiérrez
Roberto Zarama
Juan Alejandro Valdivia
author_sort Luis Fernando Gutiérrez
title Studying Three Abstract Artists Based on a Multiplex Network Knowledge Representation
title_short Studying Three Abstract Artists Based on a Multiplex Network Knowledge Representation
title_full Studying Three Abstract Artists Based on a Multiplex Network Knowledge Representation
title_fullStr Studying Three Abstract Artists Based on a Multiplex Network Knowledge Representation
title_full_unstemmed Studying Three Abstract Artists Based on a Multiplex Network Knowledge Representation
title_sort studying three abstract artists based on a multiplex network knowledge representation
publisher Hindawi-Wiley
series Complexity
issn 1099-0526
publishDate 2021-01-01
description Discovering the influences between paintings and artists is very important for automatic art analysis. Lately, this problem has gained more importance since research studies are looking into explanations about the origin and evolution of artistic styles, which is a related problem. This paper proposes to build a multiplex artwork representation based on artistic formal concepts to gain more understanding about the aforementioned problem. We complement and built our approach on the previous notion of Creativity Implication Network. We used the recently proposed MultiRank algorithm to suggest possible explanations of the dynamic of some artistic styles. Our results corroborate some well-known facts about the artists analyzed and give qualitative and quantitative information that show the possibilities and strengths of the proposed framework. We plan to expand our analysis to include more abstract artworks. Ideally, we are going to be able to validate more our results and test how our methodology could be used to generate visual artifacts too.
url http://dx.doi.org/10.1155/2021/8506571
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