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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 a semantic service-oriented approach. KnowleTracker has powerful deep mining functions to pull out news and other information that may lie several layers below the front page based on a semantic search for not only the specific keyword, but also the associated concepts that are not part of the keywords. The
Many e-commerce web sites such as online book retailers or specialized information hubs such as online movie databases make use of recommendation systems where users are directed to items of interests based on past user interactions. While keyword based approaches are naive and do not take content or context into
Systems to date have labels which are assigned by a person, e.g., tagging an object or a place with a keyword or phrase. Given some entities already labelled, a formal mechanism of generating labels using spatial context (detectable by sensors) is useful, not only to create new labellings without manual effort, but
This paper introduces an application developed with FAO Agrovoc ontology and Google AJAX API. FAO Agrovoc ontology is not only an agricultural concepts collection but also the relationships among the concepts, Google API can be used to submit keywords to Google search engine and get the retrieval results from Google
Web page recommendation model traces userspsila Web-surfing trails, extracts the useful information including keywords, Web page URLs and userspsila evaluations on Web pages, and automatically generates FCA (formal concept analysis) knowledge base and enterprise ontology knowledge base with WordNet. While users are
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