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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Data-driven learning for languages other than English: the cases of French, German, Italian, and Spanish Schaeffer-Lacroix, Eva; Jablonkai, Reka; Forti, Luciana... In: CALL for widening participation ; https://hal.archives-ouvertes.fr/hal-03547807 ; CALL for widening participation, EUROCALL 2020, Aug 2020, Copenhague, Denmark. pp.132 - 137, ⟨10.14705/rpnet.2020.48.1177⟩ ; https://research-publishing.net/manuscript?10.14705/rpnet.2020.48.1177 (2020) BASE Show details 2 Corpora for Linguists vs. Corpora for Learners ... Forti, Luciana; Spina, Stefania. - : Università Ca’ Foscari Venezia, Italia, 2020 BASE Show details 3 Learning to Classify Text Complexity for the Italian Language Using Support Vector Machines Santucci, Valentino; Forti, Luciana; Santarelli, Filippo; Spina, Stefania; Milani, Alfredo In: Computational Science and Its Applications – ICCSA 2020 (2020) Abstract: Natural language processing is undoubtedly one of the most active fields of research in the machine learning community. In this work we propose a supervised classification system that, given in input a text written in the Italian language, predicts its linguistic complexity in terms of a level of the Common European Framework of Reference for Languages (better known as CEFR). The system was built by considering: (i) a dataset of texts labeled by linguistic experts was collected, (ii) some vectorisation procedures which transform any text to a numerical representation, and (iii) the training of a support vector machine’s model. Experiments were conducted following a statistically sound design and the experimental results show that the system is able to reach a good prediction accuracy. Keyword: Article URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7978617/ https://doi.org/10.1007/978-3-030-58802-1_27 BASE Hide details 4 Data-driven learning for languages other than English: The cases of French, German, Italian, and Spanish Jablonkai, Reka; Forti, Luciana; Castelló, Magdalena Abad. - : EuroCALL, 2020 BASE Show details

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