Name
Title | ||
|---|---|---|
CC-GA: A clustering coefficient based genetic algorithm for detecting communities in social networks. |
Abstract | ||
|---|---|---|
•Using clustering coefficient for initial population results in high modularity.•Proposed community structure based mutation allows fast convergence.•CC-GA produces competitive results to nine existing algorithms on various networks. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.asoc.2017.11.014 | Applied Soft Computing |
Keywords | Field | DocType |
Community detection,Graph clustering,Genetic algorithm,Artificial intelligence,Social network analysis | Data mining,Population,Community structure,Social network,Correlation clustering,Complex network,Artificial intelligence,Clustering coefficient,Cluster analysis,Machine learning,Mathematics,Genetic algorithm | Journal |
Volume | ISSN | Citations |
63 | 1568-4946 | 12 |
PageRank | References | Authors |
0.55 | 20 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anwar Said | 1 | 19 | 2.70 |
| Rabeeh Abbasi | 2 | 135 | 15.82 |
| Onaiza Maqbool | 3 | 230 | 10.78 |
| Ali Daud | 4 | 313 | 30.17 |
| Naif Radi Aljohani | 5 | 159 | 27.35 |