| Document Date: 2008-10-27 22:59:17
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City Fredericton / Kingston / Seattle / San Jose / / Company Sun Microsystems / Database Systems / Intel / / Country United States / Canada / / / Facility University of New Brunswick / DR Pyramid / Pyramid Technique / / IndustryTerm radius k-nearest neighbor algorithm / k-nearest neighbor query processing / k-nearest neighbor algorithms / orthogonal range search / naive search increases / naive search / query processing / brute-force search / k-nearest neighbor search time / range search / approximate k-nearest neighbor search / search starts / neighbor search / k-nearest neighbor search example / data mining / search region / k-d range search / k-nearest neighbor search / k-nearest neighbor search approach / k-nearest neighbor search algorithm / search time / geographic information systems / k-nearest neighbor search performance / knearest neighbor search performance / k-nearest neighbor algorithm / on knearest neighbor search performance / / Organization Faculty of Computer Science / University of New Brunswick / / Person S. Netanyahu / / ProgrammingLanguage C++ / / ProvinceOrState New Brunswick / California / Washington / Ontario / / PublishedMedium Journal of the ACM / / Technology k-nearest neighbor algorithm / Intersection algorithm / DR Pyramid algorithm / 3 K-Nearest Neighbor Search Algorithm / k-nearest neighbor search algorithm / k-nearest neighbor algorithms / data mining / decreasing radius k-nearest neighbor algorithm / Xeon processors / Interval algorithm / /
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CCCG 2006, Kingston, Ontario, August 14–16, 2006 K-Nearest Neighbor Search using the Pyramid Technique Bradford G. Nickerson Abstract