Integración de Big Data y Machine Learning: Análisis de brechas y tendencias investigativas

Paula Andrea Rodríguez Correa; Vanessa García Pineda; Gustavo Moreno-López; Luis Fernando Garcés Giraldo; Aarón José Oré León; María Camila Bermeo Giraldo; Martha Benjumea-Arias

Integración de Big Data y Machine Learning: Análisis de brechas y tendencias investigativas

Translated title of the contribution: Big Data and Machine Learning Integration: Gap analysis and research trends

Paula Andrea Rodríguez Correa, Vanessa García Pineda, Gustavo Moreno-López, Luis Fernando Garcés Giraldo, Aarón José Oré León, María Camila Bermeo Giraldo, Martha Benjumea-Arias

Research output: Contribution to journal › Original Article › peer-review

Abstract

The integration of Big Data and Machine Learning is fundamental to data science and artificial intelligence, enabling in-depth analysis of vast datasets. This study aims to examine trends in this field. Using the PRISMA-2020 methodology, we conducted a wide-ranging bibliometric analysis to identify, gather, and evaluate pertinent literature. Our findings showcase a growing interest in this fusion in diverse industries, particularly in the past few years (2021-2023). Prominent authors Wang L and Wang J have examined thematic evolution in their study, highlighting an adaptation to current trends, including artificial intelligence and social media. Through their examination of keywords, they have revealed emerging approaches and challenges that are relevant to the continued integration of Big Data and Machine Learning in current research. This study emphasizes the ongoing relevance and vitality of these areas in academic research.

Translated title of the contribution	Big Data and Machine Learning Integration: Gap analysis and research trends
Original language	Spanish
Pages (from-to)	644-656
Number of pages	13
Journal	RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Volume	2024
Issue number	E70
State	Indexed - 2024
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2024, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.

Cite this

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title = "Integraci{\'o}n de Big Data y Machine Learning: An{\'a}lisis de brechas y tendencias investigativas",

abstract = "The integration of Big Data and Machine Learning is fundamental to data science and artificial intelligence, enabling in-depth analysis of vast datasets. This study aims to examine trends in this field. Using the PRISMA-2020 methodology, we conducted a wide-ranging bibliometric analysis to identify, gather, and evaluate pertinent literature. Our findings showcase a growing interest in this fusion in diverse industries, particularly in the past few years (2021-2023). Prominent authors Wang L and Wang J have examined thematic evolution in their study, highlighting an adaptation to current trends, including artificial intelligence and social media. Through their examination of keywords, they have revealed emerging approaches and challenges that are relevant to the continued integration of Big Data and Machine Learning in current research. This study emphasizes the ongoing relevance and vitality of these areas in academic research.",

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author = "Correa, {Paula Andrea Rodr{\'i}guez} and Pineda, {Vanessa Garc{\'i}a} and Gustavo Moreno-L{\'o}pez and Giraldo, {Luis Fernando Garc{\'e}s} and Le{\'o}n, {Aar{\'o}n Jos{\'e} Or{\'e}} and Giraldo, {Mar{\'i}a Camila Bermeo} and Martha Benjumea-Arias",

year = "2024",

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journal = "RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao",

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T2 - Análisis de brechas y tendencias investigativas

AU - Correa, Paula Andrea Rodríguez

AU - Pineda, Vanessa García

AU - Moreno-López, Gustavo

AU - Giraldo, Luis Fernando Garcés

AU - León, Aarón José Oré

AU - Giraldo, María Camila Bermeo

AU - Benjumea-Arias, Martha

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AB - The integration of Big Data and Machine Learning is fundamental to data science and artificial intelligence, enabling in-depth analysis of vast datasets. This study aims to examine trends in this field. Using the PRISMA-2020 methodology, we conducted a wide-ranging bibliometric analysis to identify, gather, and evaluate pertinent literature. Our findings showcase a growing interest in this fusion in diverse industries, particularly in the past few years (2021-2023). Prominent authors Wang L and Wang J have examined thematic evolution in their study, highlighting an adaptation to current trends, including artificial intelligence and social media. Through their examination of keywords, they have revealed emerging approaches and challenges that are relevant to the continued integration of Big Data and Machine Learning in current research. This study emphasizes the ongoing relevance and vitality of these areas in academic research.

KW - Artificial Intelligence

KW - Data Science

KW - Internet of Things

KW - PRISMA-2020

KW - Technological Innovation

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M3 - Artículo original

AN - SCOPUS:85201305524

SN - 1646-9895

VL - 2024

SP - 644

EP - 656

JO - RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao

JF - RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao

IS - E70

ER -

Integración de Big Data y Machine Learning: Análisis de brechas y tendencias investigativas

Abstract

Bibliographical note

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