In online unit clustering a set of n points of a metric space that arrive one by one, partition the points into clusters of diameter at most one, so that number of clusters is minimized. This paper gives linear upper and lower bounds for the advice complexity of 1-competitive online unit clustering algorithms in terms of number of points in $\mathbb{R}^d$ and $\mathbb{Z}^d$.

翻译：在在线单位聚类问题中，度量空间中的n个点依次到达，需要将这些点划分为直径不超过1的簇，以最小化簇的数量。本文针对$\mathbb{R}^d$和$\mathbb{Z}^d$中点的数量，给出了1-竞争在线单位聚类算法的建议复杂度的线性上界与下界。