dorsal/arxiv
View SchemaVertex similarity in networks
| Authors | E. A. Leicht, Petter Holme, M. E. J. Newman |
|---|---|
| Categories | |
| ArXiv ID | physics/0510143 |
| URL | https://arxiv.org/abs/physics/0510143 |
| DOI | 10.1103/PhysRevE.73.026120 |
| Journal | Phys. Rev. E 73, 026120 (2006) |
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.
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"abstract": "We consider methods for quantifying the similarity of vertices in networks.\nWe propose a measure of similarity based on the concept that two vertices are\nsimilar if their immediate neighbors in the network are themselves similar.\nThis leads to a self-consistent matrix formulation of similarity that can be\nevaluated iteratively using only a knowledge of the adjacency matrix of the\nnetwork. We test our similarity measure on computer-generated networks for\nwhich the expected results are known, and on a number of real-world networks.",
"arxiv_id": "physics/0510143",
"authors": [
"E. A. Leicht",
"Petter Holme",
"M. E. J. Newman"
],
"categories": [
"physics.soc-ph",
"cond-mat.dis-nn",
"physics.data-an"
],
"doi": "10.1103/PhysRevE.73.026120",
"journal_ref": "Phys. Rev. E 73, 026120 (2006)",
"title": "Vertex similarity in networks",
"url": "https://arxiv.org/abs/physics/0510143"
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