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High-dimensional indexing / Cui Yu
Titre : High-dimensional indexing : transformational approachesto high-dimensional range and similarity searches Type de document : texte imprimé Auteurs : Cui Yu Editeur : New York: Springer,Softc over : Berlin Année de publication : 2002 Importance : 152 p Format : 23.5 x 15.5 cm ISBN/ISSN/EAN : 978-3-540-44199-1 Langues : Français (fre) Mots-clés : Indexing,high dimensional Index. décimale : 005 Programmation, programmes, organisation des données, logiciel Résumé : 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 joinsHigh-dimensional indexing : transformational approachesto high-dimensional range and similarity searches [texte imprimé] / Cui Yu . - New York: Springer,Softc over : Berlin, 2002 . - 152 p ; 23.5 x 15.5 cm.
ISBN : 978-3-540-44199-1
Langues : Français (fre)
Mots-clés : Indexing,high dimensional Index. décimale : 005 Programmation, programmes, organisation des données, logiciel Résumé : 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 joinsRéservation
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