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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2508
Title: All-nearest-neighbors queries in spatial databases
Authors: Zhang, Jun
Papadias, Dimitris
Mamoulis, Nikos
Tao, Yufei
Keywords: All-nearest-neighbors queries
Spatial databases
Multidimensional objects
ANN query processing
Database indexing
Closest-pairs query processing
Issue Date: Jun-2004
Citation: Proceedings of the 16th International Conference on Scientific & Statistical Database Management, v. 16 ( 2004 ), p. 297-306
Abstract: Given two sets A and B of multidimensional objects, the all-nearest-neighbors (ANN) query retrieves for each object in A its nearest neighbor in B. Although this operation is common in several applications, it has not received much attention in the database literature. In this paper we study alternative methods for processing ANN queries depending on whether A and B are indexed. Our algorithms are evaluated through extensive experimentation using synthetic and real datasets. The performance studies show that they are an order of magnitude faster than a previous approach based on closest-pairs query processing.
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URI: http://hdl.handle.net/1783.1/2508
Appears in Collections:CSE Conference Papers

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