Predicting Judicial Outcomes in the Brazilian Legal System Using Textual Features. Bertalan, V. G. F. & Ruiz, E. E. S. abstract bibtex The combination of Natural Language Processing and Artificial Intelligence for the field of Law is a growing area, with the potential of radically changing the daily routine of legal professionals. The amount of text generated by those professionals is outstanding, and to this point, still unexplored by Computer Science. One of the most acclaimed research field covering both knowledge areas is Legal Prediction, in which intelligent systems try to predict specific judicial characteristics, such as the judicial outcome or the judicial class or a given case. This research intends to create a classifier to predict judicial outcomes in the Brazilian legal system. At first, we developed a text crawler to retrieve judicial outcomes from the official Brazilian electronic legal systems. Afterward, a few judicial subjects were selected, and some of their features were extracted. Later, a set of different classifiers was applied to predict the legal considering these textual features.
@article{bertalan_predicting_nodate,
title = {Predicting {Judicial} {Outcomes} in the {Brazilian} {Legal} {System} {Using} {Textual} {Features}},
abstract = {The combination of Natural Language Processing and Artificial Intelligence for the field of Law is a growing area, with the potential of radically changing the daily routine of legal professionals. The amount of text generated by those professionals is outstanding, and to this point, still unexplored by Computer Science. One of the most acclaimed research field covering both knowledge areas is Legal Prediction, in which intelligent systems try to predict specific judicial characteristics, such as the judicial outcome or the judicial class or a given case. This research intends to create a classifier to predict judicial outcomes in the Brazilian legal system. At first, we developed a text crawler to retrieve judicial outcomes from the official Brazilian electronic legal systems. Afterward, a few judicial subjects were selected, and some of their features were extracted. Later, a set of different classifiers was applied to predict the legal considering these textual features.},
language = {en},
author = {Bertalan, Vithor Gomes Ferreira and Ruiz, Evandro Eduardo Seron},
pages = {11},
}
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