Name
Title | ||
|---|---|---|
Detection of communities in directed networks based on strongly p-connected components |
Abstract | ||
|---|---|---|
A lot of algorithms in communities detection have been proposed particularly for undirected networks. As methods to find communities in directed networks are few, our contribution is to propose a method based on strongly and unilaterally connected components, and more specifically on strongly p-connected components in directed graphs. The result is a clustering of nodes giving good results in generated graphs according to several clustering evaluation measures, and which practical time complexity remains acceptable. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CASON.2011.6085946 | Computational Aspects of Social Networks |
Keywords | Field | DocType |
computational complexity,directed graphs,network theory (graphs),pattern clustering,clustering evaluation measure,community detection,directed graph,directed networks,strongly p-connected component,time complexity,undirected network | Graph,Computer science,Directed graph,Complex network,Artificial intelligence,Connected component,Merge (version control),Time complexity,Cluster analysis,Machine learning,Computational complexity theory | Conference |
ISBN | Citations | PageRank |
978-1-4577-1132-9 | 5 | 0.45 |
References | Authors | |
10 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincent Levorato | 1 | 5 | 0.45 |
| Coralie Petermann | 2 | 5 | 0.45 |