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Improving Information Retrieval by Meta-modelling Medical Terminologies

机译:通过元建模医学术语改善信息检索

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Abstract. 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.
机译:抽象。这项工作旨在通过对与医学有关的多种术语进行元建模来改善健康网关中的信息检索。元模型基于元术语,这些元术语收集了几个语义相关的术语。最初为MeSH词库建模的元术语已扩展到其他术语,例如IC10或SNOMED Int。在一个和多个术语的情况下,评估并比较了该模型的有用性和信息检索的相关性。结果表明,利用多种术语有助于提高召回率,但会降低准确性。

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