Abstract
One of the most representative and studied Distance-Based Queries in Spatial Databases is the K-Closest-Pairs Query (KCPQ). This query involves two spatial data sets and a distance function to measure the degree of closeness, along with a given number K of elements of the result. The output is a set of pairs of objects (with one object element from each set), with the K lowest distances. In this paper, we study the problem of processing KCPQs between RAM-based point sets, using Plane-Sweep (PS) algorithms. We utilize two improvements that can be applied to a PS algorithm and propose a new algorithm that minimizes the number of distance computations, in comparison to the classic PS algorithm. By extensive experimentation, using real and synthetic data sets, we highlight the most efficient improvement and show that the new PS algorithm outperforms the classic one, in most cases.
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