APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE AUTOMATIC IDENTIFICATION AND CLASSIFICATION REPETITIVE DEMAND RESOLUTION INCIDENT IN THE BRAZILIAN COURT OF JUSTICE

Autores/as

  • Antônio Pires Castro Júnior Universidade Federal de Goiás (UFG), Goiânia, Goiás, Brasil, apcastrojr@gmail.com
  • Gabriel A. Wainer Carleton University, Ottawa, Canada, gwainer@sce.carleton.ca
  • Wesley P. Calixto Universidade Federal de Goiás (UFG), Goiânia, Goiás, Brasil, wesley.pacheco@ufg.br

DOI:

https://doi.org/10.5216/rfd.v45i2.70086

Resumen

One of the areas of knowledge with several possibilities for applying artificial intelligence is Law. Recent changes in Brazilian legislation have facilitated the use of information technology resources to streamline the progress and judgment of cases, such as repetitive demand resolution incident (IRDRs). The aim of this paper is to develop and apply an AI method that can identify and relate new lawsuits with consolidated repetitive judgments (IRDRs). The datasets used in this research are judges' repetitive judgment documents, and consolidated in IRDRs. Court documents are transformed into weighted vectors. The construction of the weights in the vector is based on the co-occurrence of the terms, calculated from the combination of the term frequency-inverse document frequency and their similarity in the corpus of the same IRDR. Artificial neural networks are trained with these vectors to recognize whether new lawsuits are related to an IRDR. As the methodology obtained 93% accuracy, 97% precision, and 93% in recall in the simulations, the method can streamline the work of the Court of Justice, seeking to solve society’s conflicts as quickly as possible. Although the method can be used in several scenarios, the simulations were carried out in judicial documents.

Descargas

Biografía del autor/a

Wesley P. Calixto, Universidade Federal de Goiás (UFG), Goiânia, Goiás, Brasil, wesley.pacheco@ufg.br

Possui graduação em Física pela Pontifícia Universidade Católica de Goiás (2002), mestrado em Engenharia Elétrica e de Computação pela Universidade Federal de Goiás (2008) e doutorado em Engenharia Elétrica pela Universidade Federal de Uberlândia (2011) com período na Universidade de Coimbra (UC), Portugal. Realizou pós-doutorado em modelagem de sistemas eletromagnéticos aplicado a geoprospecção na Carleton University (CU), Ottawa/Canadá no Visualization and Simulation Centre (VSIM). Atualmente é docente permanente no programa de pós-graduação da Universidade Federal de Goiás e professor full do Instituto Federal de Educação, Ciência e Tecnologia de Goiás. Atua na área de modelagem de sistemas com ênfase em sistemas inteligentes, processo de otimização, modelos computacionais e inteligência artificial.

Publicado

2022-01-01

Cómo citar

CASTRO JÚNIOR, A. P.; WAINER, G. A.; CALIXTO, W. P. . APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE AUTOMATIC IDENTIFICATION AND CLASSIFICATION REPETITIVE DEMAND RESOLUTION INCIDENT IN THE BRAZILIAN COURT OF JUSTICE. Revista Facultad de Derecho UFG, Goiânia, v. 45, n. 2, 2022. DOI: 10.5216/rfd.v45i2.70086. Disponível em: https://revistas.ufg.br/revfd/article/view/70086. Acesso em: 27 dic. 2024.