Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study
cic.institucionOrigen | Laboratorio de Investigación y Formación en Informática Avanzada (LIFIA) | |
cic.isFulltext | SI | |
cic.isPeerReviewed | SI | |
cic.lugarDesarrollo | Laboratorio de Investigación y Formación en Informática Avanzada (LIFIA) | |
cic.parentType | Artículo | |
cic.version | Publicada | |
dc.date.accessioned | 2025-09-16T17:01:22Z | |
dc.date.available | 2025-09-16T17:01:22Z | |
dc.identifier.uri | https://digital.cic.gba.gob.ar/handle/11746/12553 | |
dc.title | Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study | en |
dc.type | Artículo | |
dcterms.abstract | 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. | en |
dcterms.creator.author | D’Alotto, Juan Eduardo | |
dcterms.creator.author | Pons, Claudia Fabiana | |
dcterms.creator.author | Antonelli, Leandro | |
dcterms.identifier.other | DOI: 10.24215/16666038.25.e03 | |
dcterms.identifier.other | ISSN: 1666-6038 | |
dcterms.identifier.url | http://dx.doi.org/10.24215/16666038.25.e03 | |
dcterms.isPartOf.issue | vol. 25, no. 1 | |
dcterms.isPartOf.series | Journal of Computer Science & Technology | |
dcterms.issued | 2025-04 | |
dcterms.language | Inglés | |
dcterms.license | Attribution-NonCommercial-ShareAlike 4.0 International (BY-NC-SA 4.0) | |
dcterms.subject | artificial intelligence | en |
dcterms.subject | civil law | en |
dcterms.subject | legal information retrieval | en |
dcterms.subject | automatic query expansion | en |
dcterms.subject | text classification algorithms | en |
dcterms.subject.materia | Ciencias de la Computación e Información |
Archivos
Bloque original
1 - 1 de 1
Cargando...
- Nombre:
- Artificial Intelligence Applied in Legal Information.pdf
- Tamaño:
- 1.52 MB
- Formato:
- Adobe Portable Document Format
- Descripción:
- Documento completo
Bloque de licencias
1 - 1 de 1
Cargando...
- Nombre:
- license.txt
- Tamaño:
- 3.46 KB
- Formato:
- Item-specific license agreed upon to submission
- Descripción: