Abstract
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.
Highlights
One of the main innovations in the Law area in the last years is the use of artificial intelligence (AI) in the classification and grouping of texts (CASTRO et al, 2020; RANI et al, 2017)
The method proposed collaborates with researches in the field of machine learning in text classification, in three aspects: (a) using the IRDRs of the Court of Justice of Goiás for training in AI solutions; (b) after training the AI solution, the solution will be able to relate the consolidated IRDRs to the lawsuits that come to court, and (c) develop an integration solution with the electronic process system to inform magistrates before the judgment of lawsuits
With the definition of the themes that will be used, it is necessary to separate the documents from the lawsuits to apply the computational model that can represent the document in a vector of weights, to later train the machine learning solution to predict whether a new document is related to one of the five IRDRs used in this research
Summary
One of the main innovations in the Law area in the last years is the use of artificial intelligence (AI) in the classification and grouping of texts (CASTRO et al, 2020; RANI et al, 2017). Since human resources to judge the number of lawsuits that are brought to justice is scarce, it is believed that optimization techniques with information retrieval technologies, using AI, can be applied to improve this scenario (CASTRO et al, 2017, 2017a, 2020). The change in the Brazilian Civil Procedure Code in 2015 brought the possibility of standardizing the understanding of the Brazilian Justice on legal facts and theses, and implementing, in the life of Brazilian society, the constitutional principle of isonomy. The standardization of legal understanding based on lawsuits is a raw material for information technology, especially for training in AI solutions, to frame new actions and relate to the consolidated IRDRs
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