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plus noun phrase learning for extraction of activity concepts in Chinese. We also propose an algorithm of relevance measurement for extracting relation instances by binary keywords based on co-occurrence statistics. Finally, we build a practical system of ontology learning through learning relation instances of the
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
based on keyword indexing, there are many records in their result lists that are irrelevant to the user's information needs. It is shown that for retrieving more relevant and precise results, the following two points should be concerned: First of all, the query (either it is generated by a human or an intelligent agent
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.