Archivio istituzionale della ricerca dell'Università degli Studi di Palermo
IRIS è il sistema di gestione integrata dei dati della ricerca (persone, pubblicazioni, progetti, attività) adottato dall’Università di Palermo, e ha lo scopo di raccogliere, conservare, documentare, e diffondere ad accesso aperto le informazioni relative alla produzione scientifica degli autori afferenti all’Ateneo.
EnglishIn this paper, the Automatic Text Complexity Evaluation problem is modeled as a binary classification task tackled by a Neural Network based system. It exploits Recurrent Neural Units and the Attention mechanism to measure the complexity of sentences written in the Italian language. An accurate test phase has been carried out, and the system has been compared with state-of-art tools that tackle the same problem. The computed performances proof the model suitability to evaluate sentence complexity improving the results achieved by other state-of-the-art systems.
Schicchi D., Pilato G., & Lo Bosco G. (2020). Deep neural attention-based model for the evaluation of italian sentences complexity. In Proceedings - 14th IEEE International Conference on Semantic Computing, ICSC 2020 (pp. 253-256). Institute of Electrical and Electronics Engineers Inc..
| Data di pubblicazione: | 2020 |
| Titolo: | Deep neural attention-based model for the evaluation of italian sentences complexity |
| Autori: | |
| Citazione: | Schicchi D., Pilato G., & Lo Bosco G. (2020). Deep neural attention-based model for the evaluation of italian sentences complexity. In Proceedings - 14th IEEE International Conference on Semantic Computing, ICSC 2020 (pp. 253-256). Institute of Electrical and Electronics Engineers Inc.. |
| Abstract: | In this paper, the Automatic Text Complexity Evaluation problem is modeled as a binary classification task tackled by a Neural Network based system. It exploits Recurrent Neural Units and the Attention mechanism to measure the complexity of sentences written in the Italian language. An accurate test phase has been carried out, and the system has been compared with state-of-art tools that tackle the same problem. The computed performances proof the model suitability to evaluate sentence complexity improving the results achieved by other state-of-the-art systems. |
| ISBN: | 978-1-7281-6332-1 |
| Digital Object Identifier (DOI): | 10.1109/ICSC.2020.00053 |
| Settore Scientifico Disciplinare: | Settore INF/01 - Informatica Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni |
| Appare nelle tipologie: | 2.07 Contributo in atti di convegno pubblicato in volume |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| 09031472.pdf | Versione Editoriale | Administrator Richiedi una copia |
Copyright © 2020