Tuning HeidelTime for identifying time ...
Type de document :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes
Titre :
Tuning HeidelTime for identifying time expressions in clinical texts in English and French
Auteur(s) :
Hamon, Thierry [Auteur]
Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur [LIMSI]
Université Paris 13 [UP13]
Grabar, Natalia [Auteur]
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]
Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur [LIMSI]
Université Paris 13 [UP13]
Grabar, Natalia [Auteur]
![refId](/themes/Mirage2//images/idref.png)
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]
Titre de la manifestation scientifique :
International Workshop on Health Text Mining and Information Analysis
Ville :
Gothenburg
Pays :
Suède
Date de début de la manifestation scientifique :
2014-01-01
Mot(s)-clé(s) en anglais :
Clinical texts
time expression
Natural Language Processing
time expression
Natural Language Processing
Discipline(s) HAL :
Informatique [cs]
Informatique [cs]/Informatique et langage [cs.CL]
Informatique [cs]/Informatique et langage [cs.CL]
Résumé en anglais : [en]
We present work on tuning the Heideltime system for identifying time expressions in clinical texts in English and French languages. The main amount of the method is related to the enrichment and adaptation of linguistic ...
Lire la suite >We present work on tuning the Heideltime system for identifying time expressions in clinical texts in English and French languages. The main amount of the method is related to the enrichment and adaptation of linguistic resources to identify Timex3 clinical expressions and to normalize them. The test of the adapted versions have been done on the i2b2/VA 2012 corpus for English and a collection of clinical texts for French, which have been annotated for the purpose of this study. We achieve a 0.8500 F-measure on the recognition and normalization of temporal expressions in English, and up to 0.9431 in French. Future work will allow to improve and consolidate the results.Lire moins >
Lire la suite >We present work on tuning the Heideltime system for identifying time expressions in clinical texts in English and French languages. The main amount of the method is related to the enrichment and adaptation of linguistic resources to identify Timex3 clinical expressions and to normalize them. The test of the adapted versions have been done on the i2b2/VA 2012 corpus for English and a collection of clinical texts for French, which have been annotated for the purpose of this study. We achieve a 0.8500 F-measure on the recognition and normalization of temporal expressions in English, and up to 0.9431 in French. Future work will allow to improve and consolidate the results.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :