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    A graphical self-organizing approach to classifying electronic meeting output

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    Author
    Orwig, Richard E.
    Chen, Hsinchun
    Nunamaker, Jay F.
    Issue Date
    1997-02
    Submitted date
    2004-10-29
    Keywords
    Artificial Intelligence
    Knowledge Management
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial intelligence lab
    AI lab
    
    Metadata
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    Citation
    A graphical self-organizing approach to classifying electronic meeting output 1997-02, 48(2):157-170 Journal of the American Society for Information Science
    Publisher
    Wiley Periodicals, Inc
    Journal
    Journal of the American Society for Information Science
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/105681
    Abstract
    This article describes research in the application of a Kohonen Self-Organizing Map (SOM) to the problem of classification of electronic brainstorming output and an evaluation of the results. This research builds upon previous work in automating the meeting classification process using a Hopfield neural network. Evaluation of the Kohonen output comparing it with Hopfield and human expert output using the same set of data found that the Kohonen SOM performed as well as a human expert in representing term association in the meeting output and outperformed the Hopfield neural network algorithm. Recall of consensus meeting concepts and topics using the Kohonen algorithm was equivalent to that of the human expert.
    Type
    Journal Article (Paginated)
    Language
    en
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