We consider methods for quantifying the similarity of vertices in networks.
We propose a measure of similarity based on the concept that two vertices are
similar if their immediate neighbors in the network are themselves similar.
This leads to a self-consistent matrix formulation of similarity that can be
evaluated iteratively using only a knowledge of the adjacency matrix of the
network. We test our similarity measure on computer-generated networks for
which the expected results are known, and on a number of real-world networks.
%0 Generic
%1 leicht2005vertex
%A Leicht, E. A.
%A Holme, Petter
%A Newman, M. E. J.
%D 2005
%K community network similarity sna vertex
%T Vertex similarity in networks
%U http://arxiv.org/abs/physics/0510143
%X We consider methods for quantifying the similarity of vertices in networks.
We propose a measure of similarity based on the concept that two vertices are
similar if their immediate neighbors in the network are themselves similar.
This leads to a self-consistent matrix formulation of similarity that can be
evaluated iteratively using only a knowledge of the adjacency matrix of the
network. We test our similarity measure on computer-generated networks for
which the expected results are known, and on a number of real-world networks.
@misc{leicht2005vertex,
abstract = { We consider methods for quantifying the similarity of vertices in networks.
We propose a measure of similarity based on the concept that two vertices are
similar if their immediate neighbors in the network are themselves similar.
This leads to a self-consistent matrix formulation of similarity that can be
evaluated iteratively using only a knowledge of the adjacency matrix of the
network. We test our similarity measure on computer-generated networks for
which the expected results are known, and on a number of real-world networks.
},
added-at = {2012-03-03T23:22:54.000+0100},
author = {Leicht, E. A. and Holme, Petter and Newman, M. E. J.},
biburl = {https://www.bibsonomy.org/bibtex/22e34601a4fc12f4c6a6a790971a9c44b/folke},
description = {Vertex similarity in networks},
interhash = {69083cad3fbf44bea5d31051ec7fed02},
intrahash = {2e34601a4fc12f4c6a6a790971a9c44b},
keywords = {community network similarity sna vertex},
note = {cite arxiv:physics/0510143},
timestamp = {2012-03-06T10:29:29.000+0100},
title = {Vertex similarity in networks},
url = {http://arxiv.org/abs/physics/0510143},
year = 2005
}