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

Academic Article
Publication Date:
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.
Iris type:
01.01 Articolo in rivista
Keywords:
Text simplification; Natural Language Processing; Deep Neural Networks
List of contributors:
Pilato, Giovanni
Authors of the University:
PILATO GIOVANNI
Handle:
https://iris.cnr.it/handle/20.500.14243/355678
Published in:
CEUR WORKSHOP PROCEEDINGS
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URL

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