A Review of Methods, Techniques and Algorithms for Technology Product Recommendation Systems
Descripción del Articulo
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...
| Autores: | , |
|---|---|
| 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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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 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
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article |
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https://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357 10.26439/interfases2023.n018.6357 |
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https://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357 |
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10.26439/interfases2023.n018.6357 |
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spa |
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spa |
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https://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357/6681 https://revistas.ulima.edu.pe/index.php/Interfases/article/view/6357/6884 |
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https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by/4.0 |
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openAccess |
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application/pdf text/html |
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Universidad de Lima |
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Universidad de Lima |
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Interfases; No. 018 (2023); 255-280 Interfases; Núm. 018 (2023); 255-280 Interfases; n. 018 (2023); 255-280 1993-4912 10.26439/interfases2023.n018 reponame:Revistas - Universidad de Lima instname:Universidad de Lima instacron:ULIMA |
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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 |
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13.057984 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).