A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems

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Recommendation systems are information filtering tools that help present elements to users based on their tastes and preferences, for example, making suggestions for household items or specific products for a user. Currently, there are various types of recommendation systems. recommendation (SR) to...

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Detalles Bibliográficos
Autores: Guevara Fernandez, Alexander, Coral Ygnacio, Marco A.
Formato: artículo
Fecha de Publicación:2023
Institución:Universidad de Lima
Repositorio:Revistas - Universidad de Lima
Lenguaje:español
OAI Identifier:oai:revistas.ulima.edu.pe:article/6357
Enlace del recurso:https://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357
Nivel de acceso:acceso abierto
Materia:recommender system
methods
techniques
models
algorithms
home appliances
sistema de recomendación
métodos
técnicas
modelos
algoritmos
electrodomésticos
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dc.title.none.fl_str_mv A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
Una revisión de métodos, técnicas y algoritmos para sistemas de recomendación de productos tecnológicos
title A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
spellingShingle A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
Guevara Fernandez, Alexander
recommender system
methods
techniques
models
algorithms
home appliances
sistema de recomendación
métodos
técnicas
modelos
algoritmos
electrodomésticos
title_short A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
title_full A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
title_fullStr A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
title_full_unstemmed A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
title_sort A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
dc.creator.none.fl_str_mv Guevara Fernandez, Alexander
Coral Ygnacio, Marco A.
author Guevara Fernandez, Alexander
author_facet Guevara Fernandez, Alexander
Coral Ygnacio, Marco A.
author_role author
author2 Coral Ygnacio, Marco A.
author2_role author
dc.subject.none.fl_str_mv recommender system
methods
techniques
models
algorithms
home appliances
sistema de recomendación
métodos
técnicas
modelos
algoritmos
electrodomésticos
topic recommender system
methods
techniques
models
algorithms
home appliances
sistema de recomendación
métodos
técnicas
modelos
algoritmos
electrodomésticos
description Recommendation systems are information filtering tools that help present elements to users based on their tastes and preferences, for example, making suggestions for household items or specific products for a user. Currently, there are various types of recommendation systems. recommendation (SR) to address the increase in information on the Internet by companies and thus improve efficiency in their product sales processes through recommendations. Likewise, there are different types of recommendation systems that use specific techniques that meet the business objectives such as popularity systems that focus on the popularity of a product based on the criteria of likes, comments, the time a customer took to review the product, content that based on history of a client tries to predict what the user is looking for and suggest products in relation to the client’s possible tastes and collaborative filtering in recommendation systems generate recommendations by analyzing data, identifying users and comparing the information of the user’s profile and that of a group of users, in Based on the aforementioned, this research article proposes a review of methods, techniques and algorithms for electrical product recommendation systems, with the objective of supporting and facilitating decision making as well as helping in the continuous improvement of companies and in this way increase the efficiency of the systems at the time of their implementation.
publishDate 2023
dc.date.none.fl_str_mv 2023-12-29
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
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dc.identifier.none.fl_str_mv https://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357
10.26439/interfases2023.n018.6357
url https://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357
identifier_str_mv 10.26439/interfases2023.n018.6357
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dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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dc.publisher.none.fl_str_mv Universidad de Lima
publisher.none.fl_str_mv Universidad de Lima
dc.source.none.fl_str_mv Interfases; No. 018 (2023); 255-280
Interfases; Núm. 018 (2023); 255-280
Interfases; n. 018 (2023); 255-280
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spelling A Review of Methods, Techniques and Algorithms for Technology Product Recommendation SystemsUna revisión de métodos, técnicas y algoritmos para sistemas de recomendación de productos tecnológicosGuevara Fernandez, AlexanderCoral Ygnacio, Marco A.recommender systemmethodstechniquesmodelsalgorithmshome appliancessistema de recomendaciónmétodostécnicasmodelosalgoritmoselectrodomésticosRecommendation systems are information filtering tools that help present elements to users based on their tastes and preferences, for example, making suggestions for household items or specific products for a user. Currently, there are various types of recommendation systems. recommendation (SR) to address the increase in information on the Internet by companies and thus improve efficiency in their product sales processes through recommendations. Likewise, there are different types of recommendation systems that use specific techniques that meet the business objectives such as popularity systems that focus on the popularity of a product based on the criteria of likes, comments, the time a customer took to review the product, content that based on history of a client tries to predict what the user is looking for and suggest products in relation to the client’s possible tastes and collaborative filtering in recommendation systems generate recommendations by analyzing data, identifying users and comparing the information of the user’s profile and that of a group of users, in Based on the aforementioned, this research article proposes a review of methods, techniques and algorithms for electrical product recommendation systems, with the objective of supporting and facilitating decision making as well as helping in the continuous improvement of companies and in this way increase the efficiency of the systems at the time of their implementation.Los sistemas de recomendación son herramientas de filtrado de información que ayudan a presentar elementos a los usuarios en función de sus gustos y preferencias. Por ejemplo, pueden realizar sugerencias de artículos para el hogar o productos específicos para un usuario. Actualmente, existen diversos tipos de sistemas de recomendación (SR) para abordar el incremento de información en internet por parte de las empresas y, de esa manera, mejorar la eficiencia en sus procesos de venta de productos. Así mismo, existen diferentes tipos de sistemas de recomendación que utilizan técnicas específicas para cumplir con los objetivos del rubro de la empresa. Están los sistemas de popularidad, por ejemplo, que se centran en la popularidad de un producto, teniendo como criterios los likes, comentarios, el tiempo que un cliente se tomó para revisar el producto, etcétera. También existen los de contenido que, basándose en el historial de un cliente, intentan predecir qué busca el usuario y sugerir productos en relación a posibles gustos del cliente. Finalmente, los sistemas de recomendación de filtrado colaborativo, que generan recomendaciones analizando datos, identificando usuarios y comparando la información del perfil del usuario con la de un colectivo de usuarios. En base a lo antes mencionado, en el presente artículo de investigación se propone una revisión de métodos, técnicas y algoritmos para sistemas de recomendación de productos eléctricos. El objetivo es apoyar y facilitar la toma de decisiones, así como también ayudar en el mejoramiento continuo de las empresas y, de esta manera, incrementar la eficiencia de los sistemas al momento de su implementación.Universidad de Lima2023-12-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttps://revistas.ulima.edu.pe/index.php/Interfases/article/view/635710.26439/interfases2023.n018.6357Interfases; No. 018 (2023); 255-280Interfases; Núm. 018 (2023); 255-280Interfases; n. 018 (2023); 255-2801993-491210.26439/interfases2023.n018reponame:Revistas - Universidad de Limainstname:Universidad de Limainstacron:ULIMAspahttps://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357/6681https://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357/6884https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:revistas.ulima.edu.pe:article/63572024-05-24T00:31:34Z
score 13.057984
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