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of ontology-aware keyword search of XML documents with a particular focus on EMR XML documents. Our current prototypes and experiments use the health level seven (HL7) clinical document architecture (CDA) Release 2.0 standard of EMR representation and the systematized nomenclature of human and veterinary medicine
used to associate portions of the EMR document with concepts defined in a domain ontology. In this paper we present the XOntoRank system which tackles the problem of ontology-aware keyword search on XML documents with a particular focus on EMR XML documents. Our running examples and experiments use the Health Level Seven
technique that makes use of unified medical language system, an ontology knowledge source from National Library of Medicine. We compare our method with keyword-only approach, and our ontology-based method performs clearly better. Our method also shows potential to be used in other information retrieval areas
In the viewpoint of sharing knowledge, users need to input keywords before the agent retrievals the related information from the Internet. At the same time, the traditional method ignored the true meaning of the terms. However, the semantic Web has been created to improve the disadvantage. Ontology is the fundamental
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