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Document classification using a Bi-LSTM to unclog Brazil's supreme court
November 27, 2018 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Fabricio Ataides Braz, Nilton Correia da Silva, Teofilo Emidio de Campos, Felipe Borges S. Chaves, Marcelo H. S. Ferreira, Pedro Henrique Inazawa, Victor H. D. Coelho, Bernardo Pablo Sukiennik, Ana Paula Goncalves Soares de Almeida, Flavio Barros Vidal, Davi Alves Bezerra, Davi B. Gusmao, Gabriel G. Ziegler, Ricardo V. C. Fernandes, Roberta Zumblick, Fabiano Hartmann Peixoto
arXiv ID
1811.11569
Category
cs.IR: Information Retrieval
Cross-listed
cs.LG,
stat.ML
Citations
9
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The Brazilian court system is currently the most clogged up judiciary system in the world. Thousands of lawsuit cases reach the supreme court 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 raster scanned documents with widely variable levels of quality. One of the first steps for the analysis is to classify these documents. In this paper we present a Bidirectional Long Short-Term Memory network (Bi-LSTM) to classify these pieces of legal document.
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