Ueuder Castro Do Nascimento
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Ueuder Castro Do Nascimento has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Allan Gonçalves de Oliveira
Institute of Computing, Federal University of Mato Grosso (UFMT), Brazil
1 shared publication - Cristiano Maciel
Universidade Federal de Mato Grosso
1 shared publication - Eunice Pereira dos Santos Nunes
UFMT
1 shared publication - Ingrit dos Anjos Gomes Braz
Institute of Computing, Federal University of Mato Grosso (UFMT), Brazil
1 shared publication - Josiel Maimone de Figueiredo
UFMT
1 shared publication - Luiz Augusto de Oliveira Almeida
UFMT
1 shared publication
Latest Publications
- Open Access
- 30 August 2026
- Published by TU Delft OPEN Publishing
Ethical data governance for sensitive document classification under the LGPD
This study investigates the use of the BERT model to support the automated classification of public documents according to whether they contain personal or sensitive data, in compliance with the Brazilian General Data Protection Law (LGPD). Documents from the Mato Grosso State Official Press (IOMAT) were used, comprising 1,050 documents labelled as sensitive and 450 labelled as non-sensitive. In this version, only a document-level binary classifier (sensitive vs. non-sensitive) was implemented and evaluated; Named Entity Recognition (NER), Explainable AI (XAI), and an auditing interface are described as part of a broader system planned as future work. The model — a fine-tuned BERTimbau classifier — was trained after removing explicit date expressions from the texts, with a fixed seed and deterministic settings for reproducibility. On the validation set, it reached 75.00% accuracy and an 83.66% positive-class F1-score, with a macroF1 of 65.23%. Compared with a majority-class baseline, the main improvement was observed in macro-F1, indicating that the model learned useful patterns beyond simply assigning all documents to the sensitive class. An error analysis based on the confusion matrix shows that false negatives are the legally costlier errors in a compliance setting, as they may correspond to sensitive documents being treated as non-sensitive. The results should be interpreted as preliminary and corpus-dependent, since date removal reduces but does not eliminate temporal and topical composition effects. Even so, the findings indicate the feasibility of the approach as an initial, human-in-the-loop screening stage for ethical data governance in the public sector.
- 30 August 2026
- Published by TU Delft OPEN Publishing
Open AccessEthical data governance for sensitive document classification under the LGPD
This study investigates the use of the BERT model to support the automated classification of public documents according to whether they contain personal or sensitive data, in compliance with the Brazilian General Data Protection Law (LGPD). Documents from the Mato Grosso State Official Press (IOMAT) were used, comprising 1,050 documents labelled as sensitive and 450 labelled as non-sensitive. In this version, only a document-level binary classifier (sensitive vs. non-sensitive) was implemented and evaluated; Named Entity Recognition (NER), Explainable AI (XAI), and an auditing interface are described as part of a broader system planned as future work. The model — a fine-tuned BERTimbau classifier — was trained after removing explicit date expressions from the texts, with a fixed seed and deterministic settings for reproducibility. On the validation set, it reached 75.00% accuracy and an 83.66% positive-class F1-score, with a macroF1 of 65.23%. Compared with a majority-class baseline, the main improvement was observed in macro-F1, indicating that the model learned useful patterns beyond simply assigning all documents to the sensitive class. An error analysis based on the confusion matrix shows that false negatives are the legally costlier errors in a compliance setting, as they may correspond to sensitive documents being treated as non-sensitive. The results should be interpreted as preliminary and corpus-dependent, since date removal reduces but does not eliminate temporal and topical composition effects. Even so, the findings indicate the feasibility of the approach as an initial, human-in-the-loop screening stage for ethical data governance in the public sector.
- Open Access
- 12 November 2025
- Published by Sociedade Brasileira de Computação
- p. 90-98
Registro de Metodologia para Estudo da UX em Plataformas de Governo Digital
Este artigo apresenta uma análise sobre o processo de registro de propriedade intelectual para metodologias de estudo de experiência de usuário (UX), aplicadas à eficiência operacional de plataformas de governo digital no Brasil. O estudo investiga os procedimentos legais, desafios técnicos e impactos da proteção intelectual em metodologias inovadoras de UX. A pesquisa utiliza revisão bibliográfica sistemática e análise documental para mapear o cenário atual da propriedade intelectual no país, com foco em metodologias tecnológicas e plataformas digitais governamentais.
- 12 November 2025
- Published by Sociedade Brasileira de Computação
- p. 90-98
Open AccessRegistro de Metodologia para Estudo da UX em Plataformas de Governo Digital
Este artigo apresenta uma análise sobre o processo de registro de propriedade intelectual para metodologias de estudo de experiência de usuário (UX), aplicadas à eficiência operacional de plataformas de governo digital no Brasil. O estudo investiga os procedimentos legais, desafios técnicos e impactos da proteção intelectual em metodologias inovadoras de UX. A pesquisa utiliza revisão bibliográfica sistemática e análise documental para mapear o cenário atual da propriedade intelectual no país, com foco em metodologias tecnológicas e plataformas digitais governamentais.