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                  <date type="start">2019-08-26</date>
                  <settlement>Lyon</settlement>
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                <term xml:lang="fr">Interactions aliments-médicaments</term>
                <term xml:lang="fr">Traitement Automatique des Langues</term>
                <term xml:lang="fr">Classification</term>
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              <p>Dans cet article, nous présentons le schéma d'annotation utilisé pour étudier les interactions aliments-médicaments (Food-drug interaction-FDI). Le corpus se compose de 639 résumés d'articles scientifiques issus de Medline. Nous avons défini un schéma d'annotation constitué de 21 catégories d'entités et de 21 types de relations appliquées sur 9 catégories d'entités. Ces schémas ont été appliqués sur des documents rédigés en anglais ou en français, ouvrant la voie à un corpus multilingue annoté au moyen des mêmes catégories. Nous présentons également quelques expériences d'identification automatique des types de relations. L'adaptation de domaine à partir des interactions médicament-médicament (DDI) permet d'avoir un schéma d'annotation des relations selon 4 types. L'extraction automatique de ces relations conduit à une F1-mesure de 0.79 obtenue avec un modèle SVM précédé d'un processus de sélection de descripteurs SFM.</p>
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