Databases and Information Systems Commons^™

Medoid Queries In Large Spatial Databases, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou

Kyriakos MOURATIDIS

Assume that a franchise plans to open k branches in a city, so that the average distance from each residential block to the closest branch is minimized. This is an instance of the k-medoids problem, where residential blocks constitute the input dataset and the k branch locations correspond to the medoids. Since the problem is NP-hard, research has focused on approximate solutions. Despite an avalanche of methods for small and moderate size datasets, currently there exists no technique applicable to very large databases. In this paper, we provide efficient algorithms that utilize an existing data-partition index to achieve low CPU …