Understanding of unknown medical words

Abstract : We assume that unknown words with internal structure (affixed words or compounds) can provide speakers with linguistic cues as for their meaning, and thus help their decoding and understanding. To verify this hypothesis, we propose to work with a set of French medical words. These words are annotated by five annotators. Then, two kinds of analysis are performed: analysis of the evolution of understandable and non-understandable words (globally and according to some suffixes) and anal- ysis of clusters created with unsupervised algorithms on basis of linguistic and extra-linguistic features of the studied words. Our results suggest that, according to linguistic sensitivity of annotators, technical words can be decoded and become understandable. As for the clusters, some of them distinguish between understandable and non-understandable words. Resources built in this work will be made freely available for the research purposes.
Type de document :
Communication dans un congrès
Biomedical NLP Workshop associated with RANLP 2017, Sep 2017, Varna, Bulgaria. 2017
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01736408
Contributeur : Limsi Publications <>
Soumis le : vendredi 16 mars 2018 - 21:25:11
Dernière modification le : mercredi 13 février 2019 - 01:26:23

Identifiants

  • HAL Id : hal-01736408, version 1

Citation

Natalia Grabar, Thierry Hamon. Understanding of unknown medical words. Biomedical NLP Workshop associated with RANLP 2017, Sep 2017, Varna, Bulgaria. 2017. 〈hal-01736408〉

Partager

Métriques

Consultations de la notice

53