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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Improving Information Retrieval by Meta-modelling Medical Terminologies
verfasst von : Lina F. Soualmia, Nicolas Griffon, Julien Grosjean, Stéfan J. Darmoni
Erschienen in: Artificial Intelligence in Medicine
Verlag: Springer Berlin Heidelberg
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This work aims at improving information retrieval in a health gateway by meta-modelling multiple terminologies related to medicine. The meta-model is based on meta-terms that gather several terms semantically related. Meta-terms, initially modelled for the MeSH thesaurus, are extended for other terminologies such as IC10 or SNOMED Int. The usefulness of this model and the relevance of information retrieval is evaluated and compared in the case of one and multiple terminologies. The results show that exploiting multiple terminologies contributes to increase recall but lowers precision.