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Extraction of food-drug interactions : State of the art and first results. In this paper, we are interested in the extraction of food-drug interactions (FDI), a task which is similar to the extraction of relation between terms in specialized texts. Many approaches have been proposed for extracting relations from texts, including lexico-syntactic patterns, statistical learning-based methods, and more recently deep learning-based methods. From this state of the art, we present a supervised classification method and the results of a first set of experiments. Despite the imbalance of classes, the results are encouraging. We have identified the most relevant classifiers according to the steps of our methods. We have also observed the important impact of the semantic tags of terms used as features. MOTS-CLÉS : Interaction aliment-médicament, Relation sémantique, Corpus de spécialité, Classification supervisée.

Extraction d'interactions entre aliment et médicament : Etat de l'art et premiers résultats