Deep neural attention-based model for the evaluation of italian sentences complexity

Giosue' Lo Bosco, Giovanni Pilato, Daniele Schicchi, Giovanni Pilato

Risultato della ricerca: Conference contribution

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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteProceedings - 14th IEEE International Conference on Semantic Computing, ICSC 2020
Pagine253-256
Numero di pagine4
Stato di pubblicazionePublished - 2020

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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  • Cita questo

    Lo Bosco, G., Pilato, G., Schicchi, D., & Pilato, 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 (pagg. 253-256)