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    Understanding User Intentions in Vertical Image Search

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    Chen_ku_0099M_11662_DATA_1.pdf (1.356Mb)
    Issue Date
    2011-8-31
    Author
    Chen, Yuxin
    Publisher
    University of Kansas
    Format
    74 pages
    Type
    Thesis
    Degree Level
    M.S.
    Discipline
    Electrical Engineering & 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
    With the development of Internet and Web 2.0, large volume of multimedia contents have been made online. It is highly desired to provide easy accessibility to such contents, i.e. efficient and precise retrieval of images that satisfies users' needs. Towards this goal, content-based image retrieval (CBIR) has been intensively studied in the research community, while text-based search is better adopted in the industry. Both approaches have inherent disadvantages and limitations. Therefore, unlike the great success of text search, Web image search engines are still premature. In this thesis, we present iLike, a vertical image search engine which integrates both textual and visual features to improve retrieval performance. We bridge the semantic gap by capturing the meaning of each text term in the visual feature space, and re-weight visual features according to their significance to the query terms. We also bridge the user intention gap since we are able to infer the "visual meanings" behind the textual queries. Last but not least, we provide a visual thesaurus, which is generated from the statistical similarity between the visual space representation of textual terms. Experimental results show that our approach improves both precision and recall, compared with content-based or text-based image retrieval techniques. More importantly, search results from iLike are more consistent with users' perception of the query terms.
    URI
    http://hdl.handle.net/1808/10419
    Collections
    • Engineering Dissertations and Theses [705]
    • Theses [3710]

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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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