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    Customizable and Ontology-Enhanced Medical Information Retrieval Interfaces

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    Author
    Leroy, Gondy
    Tolle, Kristin M.
    Chen, Hsinchun
    Issue Date
    1999
    Submitted date
    2004-08-16
    Keywords
    Human Computer Interaction
    Medical Libraries
    Information Seeking Behaviors
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial Intelligence lab
    AI lab
    Medical information retrieval
    Ontologies
    UMLS
    Deep semantic parsing
    
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    Citation
    Customizable and Ontology-Enhanced Medical Information Retrieval Interfaces 1999,
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/105149
    Abstract
    This paper describes the development and testing of the Medical Concept Mapper as an aid to providing synonyms and semantically related concepts to improve searching. All terms are related to the userquery and fit into the query context. The system is unique because its five components combine humancreated and computer-generated elements. The Arizona Noun Phraser extracts phrases from natural language user queries. WordNet and the UMLS Metathesaurus provide synonyms. The Arizona Concept Space generates conceptually related terms. Semantic relationships between queries and concepts are established using the UMLS Semantic Net. Two user studies conducted to evaluate the system are described.
    Type
    Conference Paper
    Language
    en
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    DLIST

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