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    An Intelligent Information Retrieval System Using Automatic Word Sense Disambiguation

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    Issue Date
    2007
    Author
    Ramasubramanian, Prasanna G.
    Agah, Arvin
    Gauch, Susan E.
    Type
    Article
    Article Version
    Scholarly/refereed, publisher version
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    Abstract
    This paper aims to establish that an intelligent contextual infonnation retrieval (IR) system can improve the quality of search results by retrieving more relevant results than those obtained with traditional search engines. Search engines capable of implicit, explicit, and no contextual retrieval were designed and implemented and their performances studied. Experimental results showed that search engines with contextual IR produce results that are more relevant, and the outcomes further indicate that there is no perceived gain in choosing specifically any one of the two approaches of implicit or explicit. The performance of the indexing mechanism, as it classifies document tokens with their appropriate contexts/word sense, was evaluated. The effectiveness of the word sense disambiguation process was found to depend to a great extent on the process (implementation) as well as the raw data (thesaurus).
    Description
    This is the published version. Copyright De Gruyter
    URI
    http://hdl.handle.net/1808/19812
    DOI
    https://doi.org/10.1515/JISYS.2008.17.4.379
    Collections
    • Electrical Engineering and Computer Science Scholarly Works [301]
    Citation
    Ramasubramanian, P.g., A. Agah, and S.e. Gauch. "An Intelligent Information Retrieval System Using Automatic Word Sense Disambiguation." Journal of Intelligent Systems 16.2 (2007): n. pag. http://dx.doi.org/10.1515/JISYS.2008.17.4.379.

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    KU Libraries
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    Lawrence, KS 66045
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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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