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Building Medical Ontologies Based on Terminology Extraction from Texts: Methodological Propositions

  • Audrey Baneyx
  • Jean Charlet
  • Marie-Christine Jaulent
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3581)

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.

Keywords

Noun Phrase Semantic Relationship Knowledge Engineer Candidate Term Lexical Unit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Audrey Baneyx
    • 1
  • Jean Charlet
    • 1
    • 2
  • Marie-Christine Jaulent
    • 1
  1. 1.INSERM, U729ParisFrance
  2. 2.STIM – DSI/AP-HP 

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