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High-Dimensional Indexing

Transformational Approaches to High-Dimensional Range and Similarity Searches

by Cui Yu
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Paperback / softback
13 November 2002
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In this monograph, we study the problem of high-dimensional indexing and systematically introduce two efficient index structures: one for range queries and the other for similarity queries. Extensive experiments and comparison studies are conducted to demonstrate the superiority of the proposed indexing methods.
Many new database applications, such as multimedia databases or stock price information systems, transform important features or properties of data objects into high-dimensional points. Searching for objects based on these features is thus a search of points in this feature space. To support efficient retrieval in such high-dimensional databases, indexes are required to prune the search space. Indexes for low-dimensional databases are well studied, whereas most of these application specific indexes are not scaleable with the number of dimensions, and they are not designed to support similarity searches and high-dimensional joins.

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    Product Details
    ISBN-13
    9783540441991
    Author
    Cui Yu
    Publisher
    Springer Nature B.V.
    Published
    13 November 2002
    Format
    Paperback / softback

    This product hasn't received any reviews yet. Be the first to review this product!

    RRP: $93.49
    $91.62
    Ships in 3-5 business days

    Delivery estimate

    Hurry up! Current stock:

    High-Dimensional Indexing

    RRP: $93.49
    $91.62

    Description

    In this monograph, we study the problem of high-dimensional indexing and systematically introduce two efficient index structures: one for range queries and the other for similarity queries. Extensive experiments and comparison studies are conducted to demonstrate the superiority of the proposed indexing methods.
    Many new database applications, such as multimedia databases or stock price information systems, transform important features or properties of data objects into high-dimensional points. Searching for objects based on these features is thus a search of points in this feature space. To support efficient retrieval in such high-dimensional databases, indexes are required to prune the search space. Indexes for low-dimensional databases are well studied, whereas most of these application specific indexes are not scaleable with the number of dimensions, and they are not designed to support similarity searches and high-dimensional joins.

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