中文说明：所提出的方法的目标是群集Ñ定点数为K群集，所以，在同一组中的对象之间的相似性是高而在不同的组中的对象之间的相似性是低。点相似性是通过投票措施，考虑到该点定义距离。使用表决制剂，聚类的问题减少到最大化的同一个群集的点之间票数的总和。它认为，基于投票最大化导致集群具有优势有关群集的紧凑，工作，以及为群集不同密度和/或尺寸。
English Description：
The goal of the proposed method is to set the number of clusters to K clusters, so the similarity between objects in the same group is high, while the similarity between objects in different groups is low. Point similarity is defined by voting measures, considering the distance of the point. Using voting agents, the clustering problem is reduced to maximize the sum of votes between points of the same cluster. It argues that vote based maximization leads to clusters having advantages related to the compactness of the clusters, working well for clusters of different densities and / or sizes.