The \(n\)-dimensional \(k\)-vector and its application to orthogonal range searching

DOI10.1016/J.AMC.2019.125010zbMath1433.68114DBLPjournals/amc/ArnasLM20arXiv2004.02335OpenAlexW2999342750WikidataQ95851548 ScholiaQ95851548MaRDI QIDQ2287830

David Arnas, Carl Leake, Daniele Mortari

Publication date: 21 January 2020

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2004.02335

zbMATH Keywords

computational geometryorthogonal range searchingmultidimensional spacesdatabase structures

Mathematics Subject Classification ID

Searching and sorting (68P10) Database theory (68P15) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05) Information storage and retrieval of data (68P20)

Related Items (1)

Range searching in multidimensional databases using navigation metadata

Cites Work

• Quad trees: A data structure for retrieval by composite keys
• Approximate range searching
• Nonlinear function inversion using \(k\)-vector
• Lower bounds for orthogonal range searching: I. The reporting case
• New Data Structures for Orthogonal Range Queries
• Multidimensional binary search trees used for associative searching
• Unnamed Item

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