Proposed extended analytic hierarchical process for selecting data science methodologies

Decision making can present a considerable amount of complexity in competitive environments; where methods that support possess great relevance. The article presents an extension of the Hierarchy Analytical Process; complemented with Personal Construct Theory, which purpose is to reduce ambiguity wh...

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Autores principales: Eckert, Karina, Britos, Paola Verónica
Formato: Articulo
Lenguaje:Inglés
Publicado: 2021
Materias:
Ciencias Informáticas
Linguistic Labels
Data Science Methodologies
Analytic Hierarchy Process
Personal Construction Theory
Etiquetas Lingüísticas
Metodologías de Ciencia de Datos
Proceso Analítico Jerárquico
Teoría de la Construcción Personal
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/118039
https://journal.info.unlp.edu.ar/JCST/article/view/1346
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-118039
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Linguistic Labels
Data Science Methodologies
Analytic Hierarchy Process
Personal Construction Theory
Etiquetas Lingüísticas
Metodologías de Ciencia de Datos
Proceso Analítico Jerárquico
Teoría de la Construcción Personal
spellingShingle Ciencias Informáticas
Linguistic Labels
Data Science Methodologies
Analytic Hierarchy Process
Personal Construction Theory
Etiquetas Lingüísticas
Metodologías de Ciencia de Datos
Proceso Analítico Jerárquico
Teoría de la Construcción Personal
Eckert, Karina
Britos, Paola Verónica
Proposed extended analytic hierarchical process for selecting data science methodologies
topic_facet Ciencias Informáticas
Linguistic Labels
Data Science Methodologies
Analytic Hierarchy Process
Personal Construction Theory
Etiquetas Lingüísticas
Metodologías de Ciencia de Datos
Proceso Analítico Jerárquico
Teoría de la Construcción Personal
description Decision making can present a considerable amount of complexity in competitive environments; where methods that support possess great relevance. The article presents an extension of the Hierarchy Analytical Process; complemented with Personal Construct Theory, which purpose is to reduce ambiguity when defining and establishing values for the criteria in a determined problem. In recent years, the scope for decision making based on data has considerably raised, which is why Data Science as a scientific field is rising in popularity; where one of the main activities for data scientists is selecting an adequate methodology to guide a project with this traits. The steps defined in the proposed model guide this task, from establishing and prioritizing criteria based on degrees of compliance, grouping them by levels, completing the hierarchical structure of the problem, performing the correct comparisons through different levels in an ascendant manner, to finally obtaining the definitive priorities of each methodology for each validation case and sorting them by their adequacy percentages. Both disparate cases, one referred to an industrial/commercial field and the other to an academic field, were effective to corroborate the extent of usefulness of the proposed model; for which in both cases MoProPEI obtained the best results.
format Articulo
Articulo
author Eckert, Karina
Britos, Paola Verónica
author_facet Eckert, Karina
Britos, Paola Verónica
author_sort Eckert, Karina
title Proposed extended analytic hierarchical process for selecting data science methodologies
title_short Proposed extended analytic hierarchical process for selecting data science methodologies
title_full Proposed extended analytic hierarchical process for selecting data science methodologies
title_fullStr Proposed extended analytic hierarchical process for selecting data science methodologies
title_full_unstemmed Proposed extended analytic hierarchical process for selecting data science methodologies
title_sort proposed extended analytic hierarchical process for selecting data science methodologies
publishDate 2021
url http://sedici.unlp.edu.ar/handle/10915/118039
https://journal.info.unlp.edu.ar/JCST/article/view/1346
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AT britospaolaveronica propuestadelprocesoanaliticojerarquicoextendidoparalaselecciondemetodologiasdecienciasdedatos
bdutipo_str Repositorios
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