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THE TENTH INTERNATIONAL CONFERENCE ON FORENSIC COMPUTER SCIENCE AND CYBER LAW - ICoFCS 2018

Print ISBN 978-85-65069-15-1, pages 7-11
DOI: 10.5769/C2018001 and http://dx.doi.org/10.5769/C2018001



Document type classification for Brazil’s supreme court using a Convolutional Neural Network

By Nilton Correia da Silva, Fabricio Ataides Braz, Teófilo Emídio de Campos, André Bernardes Soares Guedes (Alumni), Danilo Barros Mendes, Davi Alves Bezerra, Davi Benevides Gusmão, Felipe Borges de Souza Chaves, Gabriel Gomes Ziegler, Lucas Hiroshi Horinouchi, Marcelo Herton Pereira Ferreira, Pedro Henrique Gonçalves Inazawa, Victor Hugo Dias Coelho, Ricardo Vieira de Carvalho Fernandes, Fabiano Hartmann Peixoto, Mamede Said Maia Filho, Bernardo Pablo Sukiennik, Lahis da Silva Rosa, Roberta Zumblick Martins da Silva, Tainá Aguiar Junquilho, Gustavo H. T. A. Carvalho

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ABSTRACT

The Brazilian Court System is currently the biggest judiciary system in the world, and receives an extremely high number of lawsuit cases every day. These cases need to be analyzed in order to be associated to relevant tags and allocated to the right team. Most of the cases reach the court as single PDF files containing multiple documents. One of the first steps for the analysis is to classify these documents. In this paper we present results on identifying these pieces of document using a simple convolutional neural network.


KEYWORDS

Natural Language Processing, Convolutional Neural Networks, Document Classification.

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