Vertex similarity in networks

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.

• NS
  National Science Foundation
• WF
  Wenner-Gren Foundation
• UO
  University of Michigan
• NI
  National Institutes of Health
• NI
  National Institute of Child Health and Human Development