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Using attention methods to predict judicial outcomes

Vithor Gomes Ferreira BertalanEvandro Eduardo Seron Ruiz
Jul 2022
摘要
Legal Judgment Prediction is one of the most acclaimed fields for thecombined area of NLP, AI, and Law. By legal prediction we mean an intelligentsystems capable to predict specific judicial characteristics, such as judicialoutcome, a judicial class, predict an specific case. In this research, we haveused AI classifiers to predict judicial outcomes in the Brazilian legal system.For this purpose, we developed a text crawler to extract data from the officialBrazilian electronic legal systems. These texts formed a dataset ofsecond-degree murder and active corruption cases. We applied differentclassifiers, such as Support Vector Machines and Neural Networks, to predictjudicial outcomes by analyzing textual features from the dataset. Our researchshowed that Regression Trees, Gated Recurring Units and Hierarchical AttentionNetworks presented higher metrics for different subsets. As a final goal, weexplored the weights of one of the algorithms, the Hierarchical AttentionNetworks, to find a sample of the most important words used to absolve orconvict defendants.
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