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
@article{arxiv.2005.04774,
title = {PageRank and The K-Means Clustering Algorithm},
author = {Mustafa Hajij and Eyad Said and Robert Todd},
journal= {arXiv preprint arXiv:2005.04774},
year = {2021}
}