Machine Learning Process to Determine the Social Demand for IT Professional Jobs

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Machine learning is a branch of artificial intelligence that uses scientific computing, mathematics and statistics through automated techniques to solve problems based on classification, regression and clustering. Social demand refers to the need for service and product of the professional training...

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Detalles Bibliográficos
Autor: Mamani Rodriguez, Zoraida
Formato: artículo
Fecha de Publicación:2023
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Lenguaje:español
inglés
OAI Identifier:oai:ojs.csi.unmsm:article/21643
Enlace del recurso:https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643
Nivel de acceso:acceso abierto
Materia:machine learning process
clustering
k-means
social demand
IT professionals
proceso machine learning
demanda social
profesionales de TI
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spelling Machine Learning Process to Determine the Social Demand for IT Professional JobsProceso de machine learning para determinar la demanda social de puestos de empleo de profesionales de TIMamani Rodriguez, ZoraidaMamani Rodriguez, Zoraidamachine learning processclusteringk-meanssocial demandIT professionalsproceso machine learningclusteringk-meansdemanda socialprofesionales de TIMachine learning is a branch of artificial intelligence that uses scientific computing, mathematics and statistics through automated techniques to solve problems based on classification, regression and clustering. Social demand refers to the need for service and product of the professional training process, expressed by interest groups, aimed at contributing to national development, as established by the quality assurance policy of university higher education and national licensing and accreditation models. In this context, this paper conducts research based on job positions of IT professionals posted n web portals, designs a machine learning process with an unsupervised approach, extracts occupational profiles, designs a multidimensional model, applies k-means clustering when determining clusters of job positions by similarity, and reports the results obtained.El machine learning es una rama de la inteligencia artificial que utiliza la computación científica, las matemáticas y la estadística a través de técnicas automatizadas para resolver problemas basados en clasificación, regresión y clustering. La demanda social refiere a la necesidad de servicio y producto del proceso de formación profesional, que expresan los grupos de interés, orientada a contribuir al desarrollo nacional, tal como lo establecen la política de aseguramiento de la calidad de la educación superior univeristaria y los modelos de licenciamiento y acreditación nacional. En ese contexto el presente trabajo realiza una investigación a partir de los puestos de empleo de profesionales de TI publicados en los portales web, diseña un proceso de machine learning con enfoque no supervisado, extrae los perfiles ocupacionales, diseña un modelo multidimensional, aplica clustering k-means en la determinación de conglomerados de los puestos de empleo por similitud y expone los resultados obtenidos.Facultad de Ingeniería Industrial, Universidad Nacional Mayor de San Marcos2023-01-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdftext/htmltext/htmlaudio/mpegaudio/mpeghttps://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/2164310.15381/idata.v25i2.21643Industrial Data; Vol. 25 No. 2 (2022); 275-300Industrial Data; Vol. 25 Núm. 2 (2022); 275-3001810-99931560-9146reponame:Revistas - Universidad Nacional Mayor de San Marcosinstname:Universidad Nacional Mayor de San Marcosinstacron:UNMSMspaenghttps://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19236https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19237https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19238https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19239https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19240https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/1924110.15381/idata.v25i2.21643.g19078Derechos de autor 2022 Zoraida Mamani Rodriguezhttps://creativecommons.org/licenses/by/4.0/deed.es_ESinfo:eu-repo/semantics/openAccessoai:ojs.csi.unmsm:article/216432023-01-24T11:36:31Z
dc.title.none.fl_str_mv Machine Learning Process to Determine the Social Demand for IT Professional Jobs
Proceso de machine learning para determinar la demanda social de puestos de empleo de profesionales de TI
title Machine Learning Process to Determine the Social Demand for IT Professional Jobs
spellingShingle Machine Learning Process to Determine the Social Demand for IT Professional Jobs
Mamani Rodriguez, Zoraida
machine learning process
clustering
k-means
social demand
IT professionals
proceso machine learning
clustering
k-means
demanda social
profesionales de TI
title_short Machine Learning Process to Determine the Social Demand for IT Professional Jobs
title_full Machine Learning Process to Determine the Social Demand for IT Professional Jobs
title_fullStr Machine Learning Process to Determine the Social Demand for IT Professional Jobs
title_full_unstemmed Machine Learning Process to Determine the Social Demand for IT Professional Jobs
title_sort Machine Learning Process to Determine the Social Demand for IT Professional Jobs
dc.creator.none.fl_str_mv Mamani Rodriguez, Zoraida
Mamani Rodriguez, Zoraida
author Mamani Rodriguez, Zoraida
author_facet Mamani Rodriguez, Zoraida
author_role author
dc.subject.none.fl_str_mv machine learning process
clustering
k-means
social demand
IT professionals
proceso machine learning
clustering
k-means
demanda social
profesionales de TI
topic machine learning process
clustering
k-means
social demand
IT professionals
proceso machine learning
clustering
k-means
demanda social
profesionales de TI
description Machine learning is a branch of artificial intelligence that uses scientific computing, mathematics and statistics through automated techniques to solve problems based on classification, regression and clustering. Social demand refers to the need for service and product of the professional training process, expressed by interest groups, aimed at contributing to national development, as established by the quality assurance policy of university higher education and national licensing and accreditation models. In this context, this paper conducts research based on job positions of IT professionals posted n web portals, designs a machine learning process with an unsupervised approach, extracts occupational profiles, designs a multidimensional model, applies k-means clustering when determining clusters of job positions by similarity, and reports the results obtained.
publishDate 2023
dc.date.none.fl_str_mv 2023-01-24
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643
10.15381/idata.v25i2.21643
url https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643
identifier_str_mv 10.15381/idata.v25i2.21643
dc.language.none.fl_str_mv spa
eng
language spa
eng
dc.relation.none.fl_str_mv https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19236
https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19237
https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19238
https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19239
https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19240
https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/21643/19241
10.15381/idata.v25i2.21643.g19078
dc.rights.none.fl_str_mv Derechos de autor 2022 Zoraida Mamani Rodriguez
https://creativecommons.org/licenses/by/4.0/deed.es_ES
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2022 Zoraida Mamani Rodriguez
https://creativecommons.org/licenses/by/4.0/deed.es_ES
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
text/html
text/html
audio/mpeg
audio/mpeg
dc.publisher.none.fl_str_mv Facultad de Ingeniería Industrial, Universidad Nacional Mayor de San Marcos
publisher.none.fl_str_mv Facultad de Ingeniería Industrial, Universidad Nacional Mayor de San Marcos
dc.source.none.fl_str_mv Industrial Data; Vol. 25 No. 2 (2022); 275-300
Industrial Data; Vol. 25 Núm. 2 (2022); 275-300
1810-9993
1560-9146
reponame:Revistas - Universidad Nacional Mayor de San Marcos
instname:Universidad Nacional Mayor de San Marcos
instacron:UNMSM
instname_str Universidad Nacional Mayor de San Marcos
instacron_str UNMSM
institution UNMSM
reponame_str Revistas - Universidad Nacional Mayor de San Marcos
collection Revistas - Universidad Nacional Mayor de San Marcos
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repository.mail.fl_str_mv
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