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

Résumé

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.