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Atténuer les erreurs de numérisation dans la reconnaissance d'entités nommées pour les documents historiques
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In: Conférence en Recherche d'Informations et Applications (CORIA 2021) ; https://hal.archives-ouvertes.fr/hal-03320332 ; Conférence en Recherche d'Informations et Applications (CORIA 2021), ARIA : Association Francophone de Recherche d’Information (RI) et Applications, Apr 2021, Grenoble (virtuel), France. pp.1 - 7 ; http://coria.asso-aria.org/2021/articles/mini_24/main.pdf (2021)
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Terminologies augmented recurrent neural network model for clinical named entity recognition
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In: ISSN: 1532-0464 ; EISSN: 1532-0480 ; Journal of Biomedical Informatics ; https://hal.archives-ouvertes.fr/hal-02428771 ; Journal of Biomedical Informatics, Elsevier, 2020, 102, pp.103356. ⟨10.1016/j.jbi.2019.103356⟩ (2020)
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Learning for clinical named entity recognition without manual annotations
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In: Health Informatics & Administration Faculty Articles (2018)
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Quantitative Analysis of Physician language and Patient language in Social Media. ...
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Mehta, Het. - : The University of North Carolina at Chapel Hill University Libraries, 2017
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Semantic Relation Extraction. Resources, Tools and Strategies
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BeFree : a text mining system for the extraction of biomedical information from literature
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In: TDX (Tesis Doctorals en Xarxa) (2016)
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Unsupervised Event Extraction from News and Twitter ; IDEAL Computational Linguistics Prototype
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Arabic named entity recognition ; Reconocimiento de entidades nombradas en textos árabes
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Benajiba, Yassine. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2010
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Robust multilingual Named Entity Recognition with shallow semi-supervised features
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