On the assessment of deep learning models for named entity recognition of brazilian legal documents (2023)
- Authors:
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; SOUZA, ELLEN POLLIANA RAMOS - ICMC ; SILVA, NADIA FELIX FELIPE DA - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-031-49011-8_8
- Subjects: APRENDIZAGEM PROFUNDA; PROCESSAMENTO DE LINGUAGEM NATURAL; TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS; RECUPERAÇÃO DA INFORMAÇÃO; PORTUGUÊS DO BRASIL
- Keywords: Named entity recognition; Legal information retrieval
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Lecture Notes in Artificial Intelligence
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 14116, p. 93-104, 2023
- Conference titles: Conference on Artificial Intelligence - EPIA
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
ALBUQUERQUE, Hidelberg Oliveira et al. On the assessment of deep learning models for named entity recognition of brazilian legal documents. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-49011-8_8. Acesso em: 10 fev. 2026. , 2023 -
APA
Albuquerque, H. O., Souza, E. P. R., Oliveira, A. L. I. de, Macêdo, D., Zanchettin, C., Vitório, D., et al. (2023). On the assessment of deep learning models for named entity recognition of brazilian legal documents. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-49011-8_8 -
NLM
Albuquerque HO, Souza EPR, Oliveira ALI de, Macêdo D, Zanchettin C, Vitório D, Silva NFF da, Carvalho ACP de LF de. On the assessment of deep learning models for named entity recognition of brazilian legal documents [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14116 93-104.[citado 2026 fev. 10 ] Available from: https://doi.org/10.1007/978-3-031-49011-8_8 -
Vancouver
Albuquerque HO, Souza EPR, Oliveira ALI de, Macêdo D, Zanchettin C, Vitório D, Silva NFF da, Carvalho ACP de LF de. On the assessment of deep learning models for named entity recognition of brazilian legal documents [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14116 93-104.[citado 2026 fev. 10 ] Available from: https://doi.org/10.1007/978-3-031-49011-8_8 - Building a relevance feedback corpus for legal information retrieval in the real-case scenario of the Brazilian Chamber of Deputies
- Not only what, but also when: understanding brazilian political comments on legislative bills over time through stance detection and topic modeling
- Ulysses-RFSQ: a novel method to improve legal information retrieval based on relevance feedback
- PLN no Direito: REN
- Named entity recognition: a survey for the portuguese language
- Assessing the impact of stemming algorithms applied to brazilian legislative documents retrieval
- HIRS: a hybrid information retrieval system for legislative documents
- Avaliação de frameworks para recuperação de documentos legislativos: um estudo de caso na Câmara dos Deputados brasileira
- UlyssesNERQ: expanding queries from brazilian portuguese legislative documents through named entity recognition
- Ulysses Tesemõ: a new large corpus for Brazilian legal and governmental domain
Informações sobre o DOI: 10.1007/978-3-031-49011-8_8 (Fonte: oaDOI API)
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