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    Online Query Refinement on Information Retrieval Systems: A Process Model of Searched System Interactions

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    Author
    Chen, Hsinchun
    Dhar, Vasant
    Issue Date
    1990
    Submitted date
    2004-09-20
    Keywords
    Human Computer Interaction
    Information Extraction
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial intelligence lab
    AI lab
    Information retrieval
    
    Metadata
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    Citation
    Online Query Refinement on Information Retrieval Systems: A Process Model of Searched System Interactions 1990, 90(9):115-133
    Publisher
    ACM
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/105597
    Abstract
    This article reports findings of empirical research that investigated information searchers online query refinement process. Prior studies have recognized the information specialists' role in helping searchers articulate and refine queries. Using a semantic network and a Problem Behavior Graph to represent the online search our study revealed that searchers also refined their own queries in an online task environment. The information retrieval system played a passive role in assisting online query refinement, which was, however, one that confirmed Taylor's four-level query formulation model. Based on our empirical findings, we proposed using process model to facilitate and improve query refinement in an online environment. We believe incorporating this model into retrieval systems can result in the design of more "intelligent" and useful information retrieval systems.
    Type
    Conference Paper
    Language
    en
    Collections
    DLIST

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