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A Sentence based System for Measuring Syntax Complexity using a Recurrent Deep Neural Network

Articolo
Data di Pubblicazione:
2018
Abstract:
In this paper we present a deep neural network model capable of inducing the rules that identify the syntax complexity of an Italian sentence. Our system, beyond the ability of choosing if a sentence needs of simplification, gives a score that represent the confidence of the model during the process of decision making which could be representative of the sentence complexity. Experiments have been carried out on one public corpus created specifically for the problem of text-simplification.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Text simplification; Natural Language Processing; Deep Neural Networks
Elenco autori:
Pilato, Giovanni
Autori di Ateneo:
PILATO GIOVANNI
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/355678
Pubblicato in:
CEUR WORKSHOP PROCEEDINGS
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URL

http://ceur-ws.org/Vol-2244/paper_09.pdf
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