Clustering Geometrically-Modeled Points in the Aggregated Uncertainty Model

@article{Keikha2021ClusteringGP,
  title={Clustering Geometrically-Modeled Points in the Aggregated Uncertainty Model},
  author={Vahideh Keikha and Sepideh Aghamolaei and Ali Mohades and Mohammad Ghodsi},
  journal={Fundam. Informaticae},
  year={2021},
  volume={184},
  pages={205-231}
}
The k-center problem is to choose a subset of size k from a set of n points such that the maximum distance from each point to its nearest center is minimized. Let Q = {Q1, . . . , Qn} be a set of polygons or segments in the region-based uncertainty model, in which each Qi is an uncertain point, where the exact locations of the points in Qi are unknown. The geometric objects such as segments and polygons can be models of a point set. We define the uncertain version of the k-center problem as a… 

Minimum color spanning circle of imprecise points

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