Bibiliometric Analysis of the Scientific Production of Deep Learning and Big Data
No Thumbnail Available
Date
2024-03-06
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad Nacional de Cañete
Abstract
Este artículo presenta un análisis bibliométrico de la producción científica sobre aprendizaje profundo y big data a nivel mundial. Usando la R
paquete y la biblioshiny asociada, el estudio analizó 456 artículos de investigación publicados en Scopus entre 2003 y 2023. El estudio
análisis de rendimiento aplicado, análisis de palabras clave y análisis temático. China es el país con mayor producción (536 publicaciones)
seguido de India (260 publicaciones), asimismo, la mayoría de estas colaboraciones se dan desde China hasta Estados Unidos, Hong Kong, Suecia,
Australia, Pakistán, Arabia Saudita y otros países. El rápido crecimiento de las palabras clave Aprendizaje profundo, big data, sistemas de aprendizaje y datos
analítica; Demostró el interés de investigadores, profesionales de la industria, gobiernos, inversores y todos los demás actores clave en la necesidad.
para optimizar el procesamiento de información con funciones de inteligencia artificial. Finalmente, el análisis temático muestra que el predictivo
Las mejoras mediante Big Data se aplicarán a la gestión del tráfico, la atención médica y la previsión de tendencias económicas. como futuro
En el trabajo se debe considerar el Data Masking como medida de seguridad, incorporación de arquitectura multi-nube, Data Fabric y Data Mesh, para
gestionar y mejorar el intercambio de datos de diferentes fuentes
This article presents a bibliometric analysis of the scientific production on deep learning and big data worldwide. Using the R package and the associated biblioshiny, the study analyzed 456 research articles published in Scopus between 2003 and 2023. The study applied performance analysis, keyword analysis, and thematic analysis. China is the country with the highest production (536 publications) followed by India (260 publications), likewise, most of these collaborations occur from China to the United States, Hong Kong, Sweden, Australia, Pakistan, Saudi Arabia and other countries. The rapid growth of the keywords Deep learning, big data, learning systems and data analytics; It demonstrated the interest of researchers, industry professionals, governments, investors and all other key players in the need to optimize information processing with artificial intelligence features. Finally, the thematic analysis shows that the predictive improvements through Big Data will be applied to traffic management, medical care and the forecasting of economic trends. As future work, Data Masking should be considered as a security measure, incorporation of multi-cloud architecture, Data Fabric and Data Mesh, to manage and improve the exchange of data from different sources.
This article presents a bibliometric analysis of the scientific production on deep learning and big data worldwide. Using the R package and the associated biblioshiny, the study analyzed 456 research articles published in Scopus between 2003 and 2023. The study applied performance analysis, keyword analysis, and thematic analysis. China is the country with the highest production (536 publications) followed by India (260 publications), likewise, most of these collaborations occur from China to the United States, Hong Kong, Sweden, Australia, Pakistan, Saudi Arabia and other countries. The rapid growth of the keywords Deep learning, big data, learning systems and data analytics; It demonstrated the interest of researchers, industry professionals, governments, investors and all other key players in the need to optimize information processing with artificial intelligence features. Finally, the thematic analysis shows that the predictive improvements through Big Data will be applied to traffic management, medical care and the forecasting of economic trends. As future work, Data Masking should be considered as a security measure, incorporation of multi-cloud architecture, Data Fabric and Data Mesh, to manage and improve the exchange of data from different sources.
Description
Keywords
Citation
Bibiliometric Analysis of the Scientific Production of Deep Learning and Big Data , Articulo - Escuela Profesional de Ingenieria de Sistemas