Convolutional Neural Networks and Long Short-Term Memory Networks for Textual Classification of Information Access Requests

The e-sic system aims to centralize requests for access to information addressed to the Brazilian Federal Executive. However, the volume of requests received can be an impediment to responses to those requests. The purpose of this article is to create an automatic classifier for these requests. For...

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Veröffentlicht in:	Revista IEEE América Latina 2021-05, Vol.19 (5), p.826-833
Hauptverfasser:	Paiva, Eduardo, Paim, Andrea, Ebecken, Nelson
Format:	Artikel
Sprache:	eng
Schlagworte:	Access to information Artificial neural networks Classification Computer architecture Convolution Neural Network Convolutional neural networks Error functions Government Government Data Graphics processing units IEEE transactions Information dissemination Long Short-Term Memory Neural networks Recurrent neural networks Short term Social networking (online) Text Classification
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