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Incremental distance join algorithms for spatial databases
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Source International Conference on Management of Data archive
Proceedings of the 1998 ACM SIGMOD international conference on Management of data table of contents
Seattle, Washington, United States
Pages: 237 - 248  
Year of Publication: 1998
ISBN:0-89791-995-5
Also published in ...
Authors
Gísli R. Hjaltason  Computer Science Department and Center for Automation Research and Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland
Hanan Samet  Computer Science Department and Center for Automation Research and Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 11,   Downloads (12 Months): 47,   Citation Count: 45
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ABSTRACT

Two new spatial join operations, distance join and distance semi-join, are introduced where the join output is ordered by the distance between the spatial attribute values of the joined tuples. Incremental algorithms are presented for computing these operations, which can be used in a pipelined fashion, thereby obviating the need to wait for their completion when only a few tuples are needed. The algorithms can be used with a large class of hierarchical spatial data structures and arbitrary spatial data types in any dimensions. In addition, any distance metric may be employed. A performance study using R-trees shows that the incremental algorithms outperform non-incremental approaches by an order of magnitude if only a small part of the result is needed, while the penalty, if any, for the incremental processing is modest if the entire join result is required.


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  45

Collaborative Colleagues:
Gísli R. Hjaltason: colleagues
Hanan Samet: colleagues