We analytically study proximity and distance properties of various kernels and similarity measures on graphs. This helps to understand the mathematical nature of such measures and can potentially be useful for recommending the adoption of specific similarity measures in data analysis.
@article{arxiv.1802.06284,
title = {Similarities on Graphs: Kernels versus Proximity Measures},
author = {Konstantin Avrachenkov and Pavel Chebotarev and Dmytro Rubanov},
journal= {arXiv preprint arXiv:1802.06284},
year = {2018}
}