Kinetic Clustering of Points on the Line
December 14, 2015 Β· Declared Dead Β· π Theoretical Computer Science
"No code URL or promise found in abstract"
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Authors
Cristina G. Fernandes, Marcio T. I. Oshiro
arXiv ID
1512.04303
Category
cs.CG: Computational Geometry
Cross-listed
cs.DS
Citations
0
Venue
Theoretical Computer Science
Last Checked
3 months ago
Abstract
The problem of clustering a set of points moving on the line consists of the following: given positive integers n and k, the initial position and the velocity of n points, find an optimal k-clustering of the points. We consider two classical quality measures for the clustering: minimizing the sum of the clusters diameters and minimizing the maximum diameter of a cluster. For the former, we present polynomial-time algorithms under some assumptions and, for the latter, a (2.71 + epsilon)-approximation.
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