Deep Neural Attention-Based Model for the Evaluation of Italian Sentences Complexity
Daniele Schicchi, Giovanni Pilato, Giosuè Lo Bosco
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.
Topics & Concepts
Computer scienceArtificial intelligenceTask (project management)Artificial neural networkSentenceMeasure (data warehouse)ExploitRecurrent neural networkComputational complexity theoryState (computer science)Binary classificationMachine learningNatural language processingData miningAlgorithmEconomicsManagementSupport vector machineComputer securityText Readability and SimplificationNatural Language Processing TechniquesSoftware Engineering Research