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A way to automatically enrich biomedical ontologies

Lossio-Ventura Juan Antonio, Jonquet Clément, Roche Mathieu, Teisseire Maguelonne. 2016. A way to automatically enrich biomedical ontologies. In : Advances in database technology - EDBT 2016. Pitoura Evaggelia (ed.), Maabout Sofian (ed.), Koutrika Georgia (ed.), Marian Amelie (ed.), Tanca Letizia (ed.), Manolescu Ioana (ed.), Stefanidis Kostas (ed.). Konstanz : OpenProceedings, pp. 676-677. (Series) ISBN 978-3-89318-070-7 International Conference on Extending Database Technology (EDBT 2016). 19, Bordeaux, France, 15 March 2016/18 March 2016.

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Url - éditeur : https://openproceedings.org/html/pages/2016_edbt.html

Abstract : Biomedical ontologies play an important role for information extraction in the biomedical domain. We present a workflow for updating automatically biomedical ontologies, composed of four steps. We detail two contributions concerning the concept extraction and semantic linkage of extracted terminology. (Résumé d'auteur)

Mots-clés libres : Text mining, Data mining, Clustering, Polysemy, Disambiguation, BioNLP, Biomedical

Classification Agris : C30 - Documentation and information
000 - Other themes
U10 - Computer science, mathematics and statistics

Auteurs et affiliations

  • Lossio-Ventura Juan Antonio, LIRMM (FRA)
  • Jonquet Clément, LIRMM (FRA)
  • Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568
  • Teisseire Maguelonne, LIRMM (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/580894/)

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