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On a Nearest-Neighbor Problem Under Minkowski and Power Metrics for Large Data Sets

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Abstract

The paper presents the sequential and the parallel algorithm for solving the nearest-neighbor problem in the plane, based on the generalized Voronoi diagram construction. The applications of the problem are found in the areas of networking, communications, distributed systems, computer modeling and information retrieval. The input for the problem is the set of circular sites S with varying radii, the query point p and the metric (Minkowski or power) according to which the site, neighboring the query point, is to be reported. The sequential algorithm takes O(n) time to build the data structure and O(log n) time for each query. The parallel algorithm requires O(log n log) preprocessing time and O(log) query time on EREW PRAM architecture with n/log n processors. The IDG/NNM software was developed for an experimental study of the problem. The experimental results demonstrate that the Voronoi diagram method outperforms the kd tree method for all tested input configurations. The tests were conducted on large data sets, comprising thousands of generators.

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Gavrilova, M.L. On a Nearest-Neighbor Problem Under Minkowski and Power Metrics for Large Data Sets. The Journal of Supercomputing 22, 87–98 (2002). https://doi.org/10.1023/A:1014310721543

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  • DOI: https://doi.org/10.1023/A:1014310721543

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