From Global to Local in the Sneakers Universe: A Data Science Approach
- Autores
- Perdomo, Luciano; Ordinez, Leonardo
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- In Argentina there was a great growth of e-commerce due to the COVID-19 pandemic. With the aim of helping local companies to understand the market and help them in decision making, data were obtained from online shoe sales sites and with them Machine Learning models were implemented to make price predictions in sneakers. It was concluded that higher-tier companies have greater competitive advantage over lower-tier companies. Nonetheless, the cost-effective methodology used would aid local companies scale up.
Workshop: WBDMD - Base de Datos y Minería de Datos
Red de Universidades con Carreras en Informática - Materia
-
Ciencias Informáticas
E-commerce
Machine learning
Linear Regression
Random Forest
LGBM Regressor - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/130352
Ver los metadatos del registro completo
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From Global to Local in the Sneakers Universe: A Data Science ApproachPerdomo, LucianoOrdinez, LeonardoCiencias InformáticasE-commerceMachine learningLinear RegressionRandom ForestLGBM RegressorIn Argentina there was a great growth of e-commerce due to the COVID-19 pandemic. With the aim of helping local companies to understand the market and help them in decision making, data were obtained from online shoe sales sites and with them Machine Learning models were implemented to make price predictions in sneakers. It was concluded that higher-tier companies have greater competitive advantage over lower-tier companies. Nonetheless, the cost-effective methodology used would aid local companies scale up.Workshop: WBDMD - Base de Datos y Minería de DatosRed de Universidades con Carreras en Informática2021-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf333-342http://sedici.unlp.edu.ar/handle/10915/130352enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-633-574-4info:eu-repo/semantics/reference/hdl/10915/129809info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:32:47Zoai:sedici.unlp.edu.ar:10915/130352Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:32:47.97SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
From Global to Local in the Sneakers Universe: A Data Science Approach |
title |
From Global to Local in the Sneakers Universe: A Data Science Approach |
spellingShingle |
From Global to Local in the Sneakers Universe: A Data Science Approach Perdomo, Luciano Ciencias Informáticas E-commerce Machine learning Linear Regression Random Forest LGBM Regressor |
title_short |
From Global to Local in the Sneakers Universe: A Data Science Approach |
title_full |
From Global to Local in the Sneakers Universe: A Data Science Approach |
title_fullStr |
From Global to Local in the Sneakers Universe: A Data Science Approach |
title_full_unstemmed |
From Global to Local in the Sneakers Universe: A Data Science Approach |
title_sort |
From Global to Local in the Sneakers Universe: A Data Science Approach |
dc.creator.none.fl_str_mv |
Perdomo, Luciano Ordinez, Leonardo |
author |
Perdomo, Luciano |
author_facet |
Perdomo, Luciano Ordinez, Leonardo |
author_role |
author |
author2 |
Ordinez, Leonardo |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas E-commerce Machine learning Linear Regression Random Forest LGBM Regressor |
topic |
Ciencias Informáticas E-commerce Machine learning Linear Regression Random Forest LGBM Regressor |
dc.description.none.fl_txt_mv |
In Argentina there was a great growth of e-commerce due to the COVID-19 pandemic. With the aim of helping local companies to understand the market and help them in decision making, data were obtained from online shoe sales sites and with them Machine Learning models were implemented to make price predictions in sneakers. It was concluded that higher-tier companies have greater competitive advantage over lower-tier companies. Nonetheless, the cost-effective methodology used would aid local companies scale up. Workshop: WBDMD - Base de Datos y Minería de Datos Red de Universidades con Carreras en Informática |
description |
In Argentina there was a great growth of e-commerce due to the COVID-19 pandemic. With the aim of helping local companies to understand the market and help them in decision making, data were obtained from online shoe sales sites and with them Machine Learning models were implemented to make price predictions in sneakers. It was concluded that higher-tier companies have greater competitive advantage over lower-tier companies. Nonetheless, the cost-effective methodology used would aid local companies scale up. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-10 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/130352 |
url |
http://sedici.unlp.edu.ar/handle/10915/130352 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/isbn/978-987-633-574-4 info:eu-repo/semantics/reference/hdl/10915/129809 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
eu_rights_str_mv |
openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
dc.format.none.fl_str_mv |
application/pdf 333-342 |
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reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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