6533b862fe1ef96bd12c6e04
RESEARCH PRODUCT
Deep neural attention-based model for the evaluation of italian sentences complexity
Giovanni PilatoGiosuè Lo BoscoDaniele Schicchisubject
050101 languages & linguisticsExploitComputer science02 engineering and technologyText complexity evaluationMachine learningcomputer.software_genreTask (project management)Text Simplification0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMeasure (data warehouse)Deep Neural NetworksArtificial neural networkSettore INF/01 - Informaticabusiness.industryItalian languageNatural language processing05 social sciencesComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Deep learningText ComplexityBinary classification020201 artificial intelligence & image processingArtificial intelligenceTest phasebusinesscomputerSentencedescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-02-01 |