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
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/12553
Ver los metadatos del registro completo
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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 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://digital.cic.gba.gob.ar/handle/11746/12553 |
url |
https://digital.cic.gba.gob.ar/handle/11746/12553 |
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 http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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application/pdf |
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reponame:CIC Digital (CICBA) instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires instacron:CICBA |
reponame_str |
CIC Digital (CICBA) |
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CIC Digital (CICBA) |
instname_str |
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
instacron_str |
CICBA |
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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score |
13.070432 |