Conducting a Systematic Review: Trends in Machine Learning and Text Mining

Autores
Falco, Mariana; Berdiñas, Ignacio
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The main goal of a Systematic Review is to identify, evaluate, and summarize the findings of all relevant studies over a topic or an issue, making the evidence accessible to decision makers. But the process of manually conducting a systematic reviews takes a lot of time and researchers often have to limit their procedures. With the recent technological advantages, machine learning (ML) and text mining (TM) became useful to aid the systematic review process. The objective of this study is to detect the main trends of these disciplines by carrying out an analysis of a set of relevant articles, identified with a scientific database search between 2015 and 2020. Our analysis showed that mostly ML and TM techniques were applied to three steps: search, screening and data extraction. Huge progresses have been made over the years, but full automation remains a distant goal at present.
Workshop: WBDMD – Bases de Datos y Minería de Datos
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Systematic Reviews
Literature Reviews
Machine Learning
Text Mining
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/114211

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spelling Conducting a Systematic Review: Trends in Machine Learning and Text MiningFalco, MarianaBerdiñas, IgnacioCiencias InformáticasSystematic ReviewsLiterature ReviewsMachine LearningText MiningThe main goal of a Systematic Review is to identify, evaluate, and summarize the findings of all relevant studies over a topic or an issue, making the evidence accessible to decision makers. But the process of manually conducting a systematic reviews takes a lot of time and researchers often have to limit their procedures. With the recent technological advantages, machine learning (ML) and text mining (TM) became useful to aid the systematic review process. The objective of this study is to detect the main trends of these disciplines by carrying out an analysis of a set of relevant articles, identified with a scientific database search between 2015 and 2020. Our analysis showed that mostly ML and TM techniques were applied to three steps: search, screening and data extraction. Huge progresses have been made over the years, but full automation remains a distant goal at present.Workshop: WBDMD – Bases de Datos y Minería de DatosRed de Universidades con Carreras en Informática2020-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf250-259http://sedici.unlp.edu.ar/handle/10915/114211enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-4417-90-9info:eu-repo/semantics/reference/hdl/10915/113243info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T17:07:32Zoai:sedici.unlp.edu.ar:10915/114211Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 17:07:33.234SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Conducting a Systematic Review: Trends in Machine Learning and Text Mining
title Conducting a Systematic Review: Trends in Machine Learning and Text Mining
spellingShingle Conducting a Systematic Review: Trends in Machine Learning and Text Mining
Falco, Mariana
Ciencias Informáticas
Systematic Reviews
Literature Reviews
Machine Learning
Text Mining
title_short Conducting a Systematic Review: Trends in Machine Learning and Text Mining
title_full Conducting a Systematic Review: Trends in Machine Learning and Text Mining
title_fullStr Conducting a Systematic Review: Trends in Machine Learning and Text Mining
title_full_unstemmed Conducting a Systematic Review: Trends in Machine Learning and Text Mining
title_sort Conducting a Systematic Review: Trends in Machine Learning and Text Mining
dc.creator.none.fl_str_mv Falco, Mariana
Berdiñas, Ignacio
author Falco, Mariana
author_facet Falco, Mariana
Berdiñas, Ignacio
author_role author
author2 Berdiñas, Ignacio
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Systematic Reviews
Literature Reviews
Machine Learning
Text Mining
topic Ciencias Informáticas
Systematic Reviews
Literature Reviews
Machine Learning
Text Mining
dc.description.none.fl_txt_mv The main goal of a Systematic Review is to identify, evaluate, and summarize the findings of all relevant studies over a topic or an issue, making the evidence accessible to decision makers. But the process of manually conducting a systematic reviews takes a lot of time and researchers often have to limit their procedures. With the recent technological advantages, machine learning (ML) and text mining (TM) became useful to aid the systematic review process. The objective of this study is to detect the main trends of these disciplines by carrying out an analysis of a set of relevant articles, identified with a scientific database search between 2015 and 2020. Our analysis showed that mostly ML and TM techniques were applied to three steps: search, screening and data extraction. Huge progresses have been made over the years, but full automation remains a distant goal at present.
Workshop: WBDMD – Bases de Datos y Minería de Datos
Red de Universidades con Carreras en Informática
description The main goal of a Systematic Review is to identify, evaluate, and summarize the findings of all relevant studies over a topic or an issue, making the evidence accessible to decision makers. But the process of manually conducting a systematic reviews takes a lot of time and researchers often have to limit their procedures. With the recent technological advantages, machine learning (ML) and text mining (TM) became useful to aid the systematic review process. The objective of this study is to detect the main trends of these disciplines by carrying out an analysis of a set of relevant articles, identified with a scientific database search between 2015 and 2020. Our analysis showed that mostly ML and TM techniques were applied to three steps: search, screening and data extraction. Huge progresses have been made over the years, but full automation remains a distant goal at present.
publishDate 2020
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