| Nearest neighbor queries |
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International Conference on Management of Data
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Proceedings of the 1995 ACM SIGMOD international conference on Management of data
table of contents
San Jose, California, United States
Pages: 71 - 79
Year of Publication: 1995
ISBN:0-89791-731-6
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Authors
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Nick Roussopoulos
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Department of Computer Science, University of Maryland, College Park, MD
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Stephen Kelley
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Department of Computer Science, University of Maryland, College Park, MD
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Frédéric Vincent
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Department of Computer Science, University of Maryland, College Park, MD
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| Bibliometrics |
Downloads (6 Weeks): 63, Downloads (12 Months): 413, Citation Count: 246
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ABSTRACT
A frequently encountered type of query in Geographic Information Systems is to find the k nearest neighbor objects to a given point in space. Processing such queries requires substantially different search algorithms than those for location or range queries. In this paper we present an efficient branch-and-bound R-tree traversal algorithm to find the nearest neighbor object to a point, and then generalize it to finding the k nearest neighbors. We also discuss metrics for an optimistic and a pessimistic search ordering strategy as well as for pruning. Finally, we present the results of several experiments obtained using the implementation of our algorithm and examine the behavior of the metrics and the scalability of the algorithm.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 246
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Daniel Wu , Ambuj Singh , Divyakant Agrawal , Amr El Abbadi , Terence R. Smith, Efficient retrieval for browsing large image databases, Proceedings of the fifth international conference on Information and knowledge management, p.11-18, November 12-16, 1996, Rockville, Maryland, United States
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Jignesh Patel , JieBing Yu , Navin Kabra , Kristin Tufte , Biswadeep Nag , Josef Burger , Nancy Hall , Karthikeyan Ramasamy , Roger Lueder , Curt Ellmann , Jim Kupsch , Shelly Guo , Johan Larson , David De Witt , Jeffrey Naughton, Building a scaleable geo-spatial DBMS: technology, implementation, and evaluation, ACM SIGMOD Record, v.26 n.2, p.336-347, June 1997
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