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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2277
Title: Top-k spatial joins
Authors: Zhu, Manli
Papadias, Dimitris
Zhang, Jun
Lee, Dik Lun
Keywords: Database
Spatial database
Spatial joins
Issue Date: Apr-2005
Citation: IEEE transactions on knowledge and data engineering, v. 17, no. 4, April 2005, p. 567-579
Abstract: Given two spatial datasets A and B, a top-k spatial join retrieves the k objects from A or B that intersect the largest number of objects from the other dataset. Depending on the application requirements, there exist several variations of the problem. For instance, B may be a point dataset, and the goal may be to retrieve the regions of A that contain the maximum number of points. The processing of such queries with conventional spatial join algorithms is expensive. However, several improvements are possible based on the fact that we only require a small subset of the result (instead of all intersection / containments pairs). In this paper, we propose output-sensitive algorithms for top-k spatial joins that utilize a variety of optimizations for reducing the overhead.
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URI: http://hdl.handle.net/1783.1/2277
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