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Machine Learning Models for Measuring Syntax Complexity of English Text

Capitolo di libro
Data di Pubblicazione:
2020
Abstract:
In this paper we propose a methodology to assess the syntax complexity of a sentence representing it as sequence of parts-of-speech and comparing Recurrent Neural Networks and Support Vector Machine. We have carried out experiments in English language which are compared with previous results obtained for the Italian one.
Tipologia CRIS:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
text-evaluation; text-simplification; deep-learning; naturallanguage-processing
Elenco autori:
Pilato, Giovanni
Autori di Ateneo:
PILATO GIOVANNI
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/361302
Titolo del libro:
Biologically Inspired Cognitive Architectures 2019. Advances in Intelligent Systems and Computing
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