2022
DOI: 10.3390/math10091397
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Military Applications of Machine Learning: A Bibliometric Perspective

Abstract: The military environment generates a large amount of data of great importance, which makes necessary the use of machine learning for its processing. Its ability to learn and predict possible scenarios by analyzing the huge volume of information generated provides automatic learning and decision support. This paper aims to present a model of a machine learning architecture applied to a military organization, carried out and supported by a bibliometric study applied to an architecture model of a nonmilitary orga… Show more

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Cited by 19 publications
(5 citation statements)
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“…The initial phase of our literature review involved formulating the research objectives, which served as the basis for defining the scope of the study and guiding the review process [44]. The systematic review was designed to explore the current application status of recommender systems in smart city development.…”
Section: Methodsmentioning
confidence: 99%
“…The initial phase of our literature review involved formulating the research objectives, which served as the basis for defining the scope of the study and guiding the review process [44]. The systematic review was designed to explore the current application status of recommender systems in smart city development.…”
Section: Methodsmentioning
confidence: 99%
“…The methodology used in this paper is inspired on Cobo et al (2011), Carrasco-Aguilar et al (2022), Galán et al (2022), and Minhas and Sindakis (2021).…”
Section: Methodsmentioning
confidence: 99%
“…Its objective is to show the structural and dynamic aspects of scientific research to enable further interpretation. In this paper we will follow the methodology shown in Figure 1, which is inspired by Cobo (44) and Galán et al (45). The advantage of this methodology is that there are tools that allow us to carry out most of its stages, and in this study we mainly use the following tools: SciMAT (5), VOSviewer (46), and Microsoft Excel.…”
Section: Methodsmentioning
confidence: 99%
“…To carry out this study we required high-quality scientific literature published on the ACA. There are several bibliographic database options (45): Clarivate, Scopus, Google Scholar, etc.…”
Section: Data Collectionmentioning
confidence: 99%