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Conference papers

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.
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Contributor : Limsi Publications <>
Submitted on : Friday, March 16, 2018 - 9:25:11 PM
Last modification on : Sunday, May 2, 2021 - 3:30:47 AM


  • HAL Id : hal-01736408, version 1


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



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