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Qwant Research @DEFT 2019 : appariement de documents et extraction d'informations à partir de cas cliniques

Abstract : This paper reports on Qwant Research contribution to tasks 2 and 3 of the DEFT 2019’s challenge, focusing on French clinical cases analysis. Task 2 is a task on semantic similarity between clinical cases and discussions. For this task, we propose an approach based on language models and evaluate the impact on the results of different preprocessings and matching techniques. For task 3, we have developed an information extraction system yielding very encouraging results accuracy-wise. We have experimented two different approaches, one based on the exclusive use of neural networks, the other based on a linguistic analysis.
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https://hal.archives-ouvertes.fr/hal-02172582
Contributor : Christophe Servan Connect in order to contact the contributor
Submitted on : Wednesday, July 3, 2019 - 10:26:12 PM
Last modification on : Thursday, November 25, 2021 - 3:12:06 PM

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  • HAL Id : hal-02172582, version 1

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Estelle Maudet, Oralie Cattan, Maureen de Seyssel, Christophe Servan. Qwant Research @DEFT 2019 : appariement de documents et extraction d'informations à partir de cas cliniques. Atelier Défi Fouilles de Texte 2019, Jul 2019, TOULOUSE, France. ⟨hal-02172582⟩

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