High-Dimensional Indexing: Transformational Approaches to High-Dimensional Range and Similarity Searches (Lecture Notes in Computer Science) Cui Yu

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Published: December 16th 2002

Kindle Edition

152 pages


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High-Dimensional Indexing: Transformational Approaches to High-Dimensional Range and Similarity Searches (Lecture Notes in Computer Science)  by  Cui Yu

High-Dimensional Indexing: Transformational Approaches to High-Dimensional Range and Similarity Searches (Lecture Notes in Computer Science) by Cui Yu
December 16th 2002 | Kindle Edition | PDF, EPUB, FB2, DjVu, AUDIO, mp3, RTF | 152 pages | ISBN: | 5.77 Mb

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 conductedMoreIn 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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