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            Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

            Bologna, Italy, March 1-3, 2021

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            Download Url(s)
            https://books.openedition.org/aaccademia/8203
            Contributor(s)
            Dell'Orletta, Felice (editor)
            Monti, Johanna (editor)
            Tamburini, Fabio (editor)
            Language
            English
            Show full item record
            Abstract
            On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges.
            URI
            https://directory.doabooks.org/handle/20.500.12854/87142
            Keywords
            Computational Linguistics; Fine-grained sentiment analysis; Distributional Semantics; Quantitative Linguistic Investigations; Gender Bias; Depression from Social Media; Online Hate Speech; Automatic Sarcasm Detection; TrAVaSI; AriEmozione; AEREST; COVID-1
            DOI
            10.4000/books.aaccademia.8203
            ISBN
            9791280136336
            Publisher
            Accademia University Press
            Publisher website
            http://books.openedition.org/aaccademia
            Publication date and place
            Torino, 2020
            Series
            Collana dell'Associazione Italiana di Linguistica Computazionale,
            Classification
            Language: history and general works
            Pages
            487
            Rights
            https://www.openedition.org/6540?lang=en
            • Imported or submitted locally

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            Credits


            • logo Investir l'avenirInvestir l'avenir
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            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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