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    Document similarity based on concept tree distance

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    Lakkaraju_Praveen_2007_5349267.pdf (363.3Kb)
    Issue Date
    2007-05-31
    Author
    Lakkaraju, Praveen
    Publisher
    University of Kansas
    Type
    Thesis
    Degree Level
    M.S.
    Discipline
    Electrical Engineering and Computer Science
    Rights
    This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
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    Abstract
    The Web is fast moving from an era of search engines to an era of discovery engines. Discovery engines help you find things that you never knew existed or did not know how to ask for. One of the ways this can be done is by automatically computing and displaying objects that are similar to the object in which the user is currently expressing interest. In this paper, we present a new approach to compute interdocument similarity that is based on a tree-matching algorithm. We represent each document as a concept tree using the concept associations obtained from a classifier. We make use of a tree-matching algorithm called the tree edit distance to compute similarities between these concept trees. Experiments on a subset of documents from the CiteSeer collection showed that our algorithm performed better than the document similarity based on the traditional vector space model.
    Description
    Thesis (M.S.)--University of Kansas, Electrical Engineering and Computer Science, 2007.
    URI
    http://hdl.handle.net/1808/32041
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    • Theses [3827]

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    KU Libraries
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    785-864-8983

    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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