Given two datasets DA and DB the closest-pair query (CPQ) retrieves the pair (a,b), where a ε DA and b εD B, having the smallest distance between all pairs of objects. An extension to this problem is to generate the k closest pairs of objects (k-CPQ). In several cases spatial constraints are applied, and object pairs that are retrieved must also satisfy these constraints. Although the application of spatial constraints seems natural towards a more focused search, only recently they have been studied for the CPQ problem with the restriction that D A = DB· In this work we focus on constrained closest-pair queries (CCPQ), between two distinct datasets DA and DB, where objects from DA must be enclosed by a spatial region R. A new algorithm is proposed, which is compared with a modified closest-pair algorithm. The experimental results demonstrate that the proposed approach is superior with respect to CPU and I/O costs. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Papadopoulos, A. N., Nanopoulos, A., & Manolopoulos, Y. (2005). Closest pair queries with spatial constraints. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3746 LNCS, pp. 1–13). Springer Verlag. https://doi.org/10.1007/11573036_1
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