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Machine learning in industrialization: a bibliometric analysis
Aprendizaje automático en la industrialización: un análisis bibliométrico
DOI:
https://doi.org/10.15446/dyna.v92n235.115909Palabras clave:
machine learning, industrialization, bibliometrics, artificial intelligence, supervised learning, unsupervised learning, reinforcement learning (en)aprendizaje automático, industrialización, bibliometría, inteligencia artificial, aprendizaje supervisado, aprendizaje no supervisado, aprendizaje reforzado (es)
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Machine learning is currently emerging as one of the most rapidly advancing technologies, with a recent upward trend in its use for process automation across industrial processes. The objective of this study was to conduct a bibliometric analysis to identify research trends in machine learning. The Scopus database was used to identify scientific production. Bibliometric indicators of visibility, impact, and concurrence were analyzed. The analysis of 7,335 documents, involving 22,383 authors, showed a growth rate of 20.86% from 1988 to early 2024. Three dominant research trends were identified: the first based on machine learning applications in industrial processes, the second referring to the human factor and artificial intelligence, and the third related to convolutional neural networks.
El machine learning es una de las tecnologías en auge actualmente, en los últimos años se ha observado una tendencia en su uso en la industria para la automatización de procesos. El objetivo de este estudio fue desarrollar un estudio bibliométrico para identificar las tendencias de investigación sobre machine learning en la industrialización. Se utilizó la base de datos Scopus para la identificación de la producción científica. Se analizaron indicadores bibliométricos de visibilidad, impacto y concurrencia. El análisis a partir de 7335 documentos, con la participación de 22383 autores, evidenció un crecimiento con una tasa de 20.86% en el intervalo de tiempo desde 1988 hasta inicios de 2024. Se identificaron tendencias dominantes al tema de investigación: la primera basada en la industria y el machine learning la segunda referida al factor humano y la inteligencia artificial, y la tercera relacionada con las redes neuronales convolucionales.
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