Vertex similarity in networks
| dc.creator | Leicht, E. A. | |
| dc.creator | Holme, Petter | |
| dc.creator | Newman, M. E. J. | |
| dc.date | 2005-10-14 | |
| dc.date.accessioned | 2026-07-07T06:48:28Z | |
| dc.date.available | 2026-07-07T06:48:28Z | |
| dc.description | 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. | |
| dc.identifier | https://arxiv.org/abs/physics/0510143 | |
| dc.identifier | http://arxiv.org/abs/physics/0510143 | |
| dc.identifier | Phys. Rev. E 73, 026120 (2006) | |
| dc.identifier | doi:10.1103/PhysRevE.73.026120 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/104011 | |
| dc.subject | Physics and Society | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.subject | Data Analysis, Statistics and Probability | |
| dc.title | Vertex similarity in networks | |
| dc.type | text |