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Vertex similarity in networks (2005)

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.

Publication details
Download http://arxiv.org/abs/physics/0510143
Repository arXiv (United States)
Keywords Physics - Physics and Society, Condensed Matter - Disordered Systems and Neural Networks, Physics - Data Analysis, Statistics and Probability
Type text