Name
Abstract | ||
|---|---|---|
A prominent parameter in the context of network analysis, originally proposed by Watts and Strogatz (1998), is the clustering coefficient of a graph G. It is defined as the arithmetic mean of the clustering coefficients of its vertices, where the clustering coefficient of a vertex u of G is the relative density m(G[NG(u)])∕dG(u)2 of its neighborhood if dG(u) is at least 2, and 0 otherwise. It is unknown which graphs maximize the clustering coefficient among all connected graphs of given order and size. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.disc.2017.08.020 | Discrete Mathematics |
Keywords | Field | DocType |
Clustering coefficient,Connected caveman graph,Cliquishness | k-medians clustering,Discrete mathematics,Combinatorics,Indifference graph,Correlation clustering,Vertex (geometry),Chordal graph,Watts and Strogatz model,Cluster analysis,Clustering coefficient,Mathematics | Journal |
Volume | Issue | ISSN |
341 | 1 | 0012-365X |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Gentner | 1 | 22 | 4.46 |
| Irene Heinrich | 2 | 0 | 1.01 |
| Simon Jäger | 3 | 2 | 0.81 |
| Dieter Rautenbach | 4 | 946 | 138.87 |