Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study

Autores
D’Alotto, Juan Eduardo; Pons, Claudia Fabiana; Antonelli, Leandro
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Advanced technologies, particularly Artificial Intelligence (AI), are transforming how legal professionals handle civil law relationships and daily processes. Legal Information Retrieval (LIR), a significant field within AI, focuses on efficiently identifying and analyzing legal norms and documents relevant to users' specific information needs. This systematic mapping study identifies and synthesizes primary approaches, trends, and advancements in applying AI to LIR. By reviewing recent research, it provides an overview of employed strategies, AI techniques, and emerging areas of focus. Systematic search methods were applied to academic databases, selecting relevant studies published over the past fifteen years. From 3405 initially identified articles, 34 were selected for in-depth analysis after applying inclusion and exclusion criteria. The findings reveal sustained interest in AI techniques for LIR, with a clear trend toward adopting Natural Language Processing (NLP) and machine learning to enhance search relevance, precision, and automation of legal processes. This study emphasizes the potential of AI in the legal domain and highlights the need for continued research to address unique LIR challenges in a rapidly evolving technological landscape.
Materia
Ciencias de la Computación e Información
artificial intelligence
civil law
legal information retrieval
automatic query expansion
text classification algorithms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/12553

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network_acronym_str CICBA
repository_id_str 9441
network_name_str CIC Digital (CICBA)
spelling Artificial Intelligence Applied in Legal Information: A Systematic Mapping StudyD’Alotto, Juan EduardoPons, Claudia FabianaAntonelli, LeandroCiencias de la Computación e Informaciónartificial intelligencecivil lawlegal information retrievalautomatic query expansiontext classification algorithmsAdvanced technologies, particularly Artificial Intelligence (AI), are transforming how legal professionals handle civil law relationships and daily processes. Legal Information Retrieval (LIR), a significant field within AI, focuses on efficiently identifying and analyzing legal norms and documents relevant to users' specific information needs. This systematic mapping study identifies and synthesizes primary approaches, trends, and advancements in applying AI to LIR. By reviewing recent research, it provides an overview of employed strategies, AI techniques, and emerging areas of focus. Systematic search methods were applied to academic databases, selecting relevant studies published over the past fifteen years. From 3405 initially identified articles, 34 were selected for in-depth analysis after applying inclusion and exclusion criteria. The findings reveal sustained interest in AI techniques for LIR, with a clear trend toward adopting Natural Language Processing (NLP) and machine learning to enhance search relevance, precision, and automation of legal processes. This study emphasizes the potential of AI in the legal domain and highlights the need for continued research to address unique LIR challenges in a rapidly evolving technological landscape.2025-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/12553enginfo:eu-repo/semantics/altIdentifier/doi/10.24215/16666038.25.e03info:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:39:56Zoai:digital.cic.gba.gob.ar:11746/12553Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:39:57.044CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
title Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
spellingShingle Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
D’Alotto, Juan Eduardo
Ciencias de la Computación e Información
artificial intelligence
civil law
legal information retrieval
automatic query expansion
text classification algorithms
title_short Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
title_full Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
title_fullStr Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
title_full_unstemmed Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
title_sort Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
dc.creator.none.fl_str_mv D’Alotto, Juan Eduardo
Pons, Claudia Fabiana
Antonelli, Leandro
author D’Alotto, Juan Eduardo
author_facet D’Alotto, Juan Eduardo
Pons, Claudia Fabiana
Antonelli, Leandro
author_role author
author2 Pons, Claudia Fabiana
Antonelli, Leandro
author2_role author
author
dc.subject.none.fl_str_mv Ciencias de la Computación e Información
artificial intelligence
civil law
legal information retrieval
automatic query expansion
text classification algorithms
topic Ciencias de la Computación e Información
artificial intelligence
civil law
legal information retrieval
automatic query expansion
text classification algorithms
dc.description.none.fl_txt_mv Advanced technologies, particularly Artificial Intelligence (AI), are transforming how legal professionals handle civil law relationships and daily processes. Legal Information Retrieval (LIR), a significant field within AI, focuses on efficiently identifying and analyzing legal norms and documents relevant to users' specific information needs. This systematic mapping study identifies and synthesizes primary approaches, trends, and advancements in applying AI to LIR. By reviewing recent research, it provides an overview of employed strategies, AI techniques, and emerging areas of focus. Systematic search methods were applied to academic databases, selecting relevant studies published over the past fifteen years. From 3405 initially identified articles, 34 were selected for in-depth analysis after applying inclusion and exclusion criteria. The findings reveal sustained interest in AI techniques for LIR, with a clear trend toward adopting Natural Language Processing (NLP) and machine learning to enhance search relevance, precision, and automation of legal processes. This study emphasizes the potential of AI in the legal domain and highlights the need for continued research to address unique LIR challenges in a rapidly evolving technological landscape.
description Advanced technologies, particularly Artificial Intelligence (AI), are transforming how legal professionals handle civil law relationships and daily processes. Legal Information Retrieval (LIR), a significant field within AI, focuses on efficiently identifying and analyzing legal norms and documents relevant to users' specific information needs. This systematic mapping study identifies and synthesizes primary approaches, trends, and advancements in applying AI to LIR. By reviewing recent research, it provides an overview of employed strategies, AI techniques, and emerging areas of focus. Systematic search methods were applied to academic databases, selecting relevant studies published over the past fifteen years. From 3405 initially identified articles, 34 were selected for in-depth analysis after applying inclusion and exclusion criteria. The findings reveal sustained interest in AI techniques for LIR, with a clear trend toward adopting Natural Language Processing (NLP) and machine learning to enhance search relevance, precision, and automation of legal processes. This study emphasizes the potential of AI in the legal domain and highlights the need for continued research to address unique LIR challenges in a rapidly evolving technological landscape.
publishDate 2025
dc.date.none.fl_str_mv 2025-04
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info:eu-repo/semantics/publishedVersion
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.24215/16666038.25.e03
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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collection CIC Digital (CICBA)
instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
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institution CICBA
repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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