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.
Machine Learning Models for Measuring Syntax Complexity of English Text
Giovanni Pilato
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.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
prod_404516-doc_140983.pdf
solo utenti autorizzati
Descrizione: Machine Learning Models for Measuring Syntax Complexity of English Text
Tipologia:
Documento in Pre-print
Licenza:
Nessuna licenza dichiarata (non attribuibile a prodotti successivi al 2023)
Dimensione
151.36 kB
Formato
Adobe PDF
|
151.36 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
