Abstract
In the medical field, it is now established that the maintenance of unambiguous thesauri is accomplished by the building of ontologies. Our task in the PertoMed project is to help pneumologists code acts and diagnoses with a software that represents medical knowledge by an ontology of the concerned specialty. We apply natural language processing tools to corpora to develop the resources needed to build this ontology. In this paper, our objective is to develop a methodology for the knowledge engineer to build various types of medical ontologies based on terminology extraction from texts according to the differential semantics theory. Our main research hypothesis concerns the joint use of two methods: distributional analysis and recognition of semantic relationships by lexico-syntactic patterns. The expected result is the building of an ontology of pneumology.
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References
Rector, A.: Thesauri and formal classifications: Terminologies for people and machines. Methods of Information in Medicine 37, 501–509 (1998)
Staab, S., Studer, R.: Handbook on Ontologies, 1st edn. Springer, Heidelberg (2003)
Charlet, J., Bachimont, B., Jaulent, M.: Building medical ontologies by terminology extraction from texts: An experiment for the intensive care units. Computer in Biology and Medicine (2005) (to appear)
Bachimont, B., Isaac, A., Troncy, R.: Semantic commitment for designing ontologies: A proposal. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 114–121. Springer, Heidelberg (2002)
Harris, Z.: Mathematical Structures of Language. John Wiley and Sons, NewYork (1968)
Le Moigno, S., Charlet, J., Bourigault, D., Degoulet, P., Jaulent, M.: Terminology extraction from text to build an ontology in surgical intensive care. In: Proceedings of the AMIA Annual Symposium 2002, San Antonio, Texas, pp. 430–435 (2002)
Malaisé, V., Zweigenbaum, P., Bachimont, B.: Mining defining contexts to help structuring differential ontologies. In: Ibekwe-San, J., Condamines, A., Cabré, T. (eds.) Application-Driven Terminology Engineering, Termonology, pp. 21–53. John Benjamins, Amsterdam (2005)
Hearst, M.: Automatic acquisition of hyponyms from large text corpora. In: Zampolli, A. (ed.) Proceedings of the 14th COLING, Nantes, France, pp. 539–545 (1992)
Trombert-Paviot, B., Rodrigues, J., Rogers, J., Baud, R., van der Haring, E., Rassinoux, A., Abrial, V., Clavel, L., Idir, H.: Galen: a third generation terminology tool to support a multipurpose national coding system for surgical procedures. International Journal of Medical Informatics 58-59, 71–85 (2000)
Zweigenbaum, P., Bouaud, J., Bachimont, B., Charlet, J., Séroussi, B., Boisvieux, J.F.: From text to knowledge: a unifying document-oriented view of analyzed medical language. Methods of Information in Medicine 37, 384–393 (1998)
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Baneyx, A., Charlet, J., Jaulent, MC. (2005). Building Medical Ontologies Based on Terminology Extraction from Texts: Methodological Propositions. In: Miksch, S., Hunter, J., Keravnou, E.T. (eds) Artificial Intelligence in Medicine. AIME 2005. Lecture Notes in Computer Science(), vol 3581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527770_33
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DOI: https://doi.org/10.1007/11527770_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27831-3
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