Before revision: We revisit the online Unit Clustering problem in higher dimensions: Given a set of n points in \mathbb{R , that arrive one by one,  partition the points into  clusters (subsets) of diameter at most one , so as to minimize the number of clusters used .
After revision: We revisit the online Unit Clustering problem in higher dimensions: Given a set of n points in a metric space , that arrive one by one, partition the points into clusters (subsets) of diameter at most one , so as to minimize the number of clusters used .