On the application of machine learning in astronomy and astrophysics: A text-mining-based scientometric analysis
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Universidad Politécnica de Cartagena; Universidad de Granada; Universidad de MálagaFecha de publicación
2022-09-15Editorial
WileyCita bibliográfica
Rodríguez, J.-V., Rodríguez-Rodríguez, I., & Woo, W. L. (2022). On the application of machine learning in astronomy and astrophysics: A text-mining-based scientometric analysis. WIREs Data Mining and Knowledge Discovery, 12( 5), e1476. https://doi.org/10.1002/widm.1476Revisión por pares
SIPalabras clave
AstronomyAstrophysics
Machine learning
Scientometrics
Text mining
Resumen
Since the beginning of the 21st century, the fields of astronomy and astrophysics have experienced significant growth at observational and computational levels, leading to the acquisition of increasingly huge volumes of data. In order to process this vast quantity of information, artificial intelligence (AI) techniques are being combined with data mining to detect patterns with the aim of modeling, classifying or predicting the behavior of certain astronomical phenomena or objects. Parallel to the exponential development of the aforementioned techniques, the scientific output related to the application of AI and machine learning (ML) in astronomy and astrophysics has also experienced considerable growth in recent years. Therefore, the increasingly abundant articles make it difficult to monitor this field in terms of which research topics are the most prolific or novel, or which countries or authors are leading them. In this article, a text-mining-based scientometric analysis of scientific ...
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