We utilize the PageRank vector to generalize the $k$-means clustering algorithm to directed and undirected graphs. We demonstrate that PageRank and other centrality measures can be used in our setting to robustly compute centrality of nodes in a given graph. Furthermore, we show how our method can be generalized to metric spaces and apply it to other domains such as point clouds and triangulated meshes
翻译:我们使用PageRank矢量将$k美元手段的组合组合算法推广到定向和非定向图表。我们证明,在我们的环境下,PageRank和其他中心度措施可用于在特定图表中有力地计算节点的中心点。此外,我们展示了如何将我们的方法推广到计量空间,并将其应用到其他领域,如点云和三角间距等。