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dc.contributor.supervisor Osborn, Wendy
dc.contributor.author Gong, Peng
dc.contributor.author University of Lethbridge. Faculty of Arts and Science
dc.date.accessioned 2016-01-15T23:13:12Z
dc.date.available 2016-01-15T23:13:12Z
dc.date.issued 2015
dc.identifier.uri https://hdl.handle.net/10133/3865
dc.description.abstract This thesis proposes a k-nearest-neighbor search method inspired by the grid space partitioning and the compact trie tree structure. A detailed implementation based on the Best-First-Nearest-Neighbor-Search scheme is presented and illustrated with sample data. Then k-nearest-neighbor search performance comparison is carried out among the proposed compact-trie-based method, the brute-force method, and the k-d tree based method, with one million two-dimensional spatial points and k up to 1000. The result of the comparison shows that the proposed method can perform up to 300 times better than the other two methods when k is small, suggesting that the proposed method might be suitable for low dimensions and location-dependent spatial queries in mobile computing. en_US
dc.language.iso en_CA en_US
dc.publisher Lethbridge, Alta : University of Lethbridge, Dept. of Mathematics and Computer Science en_US
dc.relation.ispartofseries Thesis (University of Lethbridge. Faculty of Arts and Science) en_US
dc.subject nearest neighbor search en_US
dc.subject trie en_US
dc.title A nearest neighbor search method suitable for low dimensions and location-dependent spatial queries in mobile computing en_US
dc.type Thesis en_US
dc.publisher.faculty Arts and Science en_US
dc.publisher.department Department of Mathematics and Computer Science en_US
dc.degree.level Masters en_US
dc.proquest.subject 0984 en_US
dc.proquest.subject 0800 en_US
dc.proquest.subject 0366 en_US
dc.proquestyes Yes en_US
dc.embargo No en_US


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