Classification of lawsuits according to the Sustainable Development Goals of the UN 2030 Agenda
DOI:
https://doi.org/10.36428/revistadacgu.v14i26.548Keywords:
UN 2030 Agenda. Natural Language Processing. Machine Learning. Neural Network.Abstract
ABSTRACT
Since 2020, the Brazilian Federal Supreme Court has classified its cases according to the sustainable development goals (SDGs) of the the United Nations 2030 Agenda. In this context, a tool for technological support to classification has immense potential to automate the manual and repetitive tasks of reading the text and registering the labels. The RAFA 2030 initiative came up with the goal of helping to classify cases. This article aims to present an integration between Agenda 2030, the work routine in STF and technical aspects of development about RAFA 2030. Currently, the main results of this project consist of graphical tools for NLP (co-occurrence graphs, tool cloud), machine learning keys, neural networks, context search and keyword counting, in addition to other tools available in R. (Shiny) and Python (Keras, Tensorflow and Pytorch). Initial results indicate great potential for applications of NLP documents and machine learning of legal documents in Agenda 2030 themes.
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