Kinetic Clustering of Points on the Line
Computational Geometry
2015-12-23 v1 Data Structures and Algorithms
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.
Keywords
Cite
@article{arxiv.1512.04303,
title = {Kinetic Clustering of Points on the Line},
author = {Cristina G. Fernandes and Marcio T. I. Oshiro},
journal= {arXiv preprint arXiv:1512.04303},
year = {2015}
}