Name
Abstract | ||
|---|---|---|
With increasing popularity and complexity of social networks, community detection in these networks has become an important research area. Several algorithms are available to detect overlapping community structures based on different approaches. Here we propose a two step genetic algorithm to detect overlapping communities based on node representation. First, we find disjoint communities and these disjoint communities are used to find overlapping communities. We use modularity as our optimization function. Experiments are performed on both artificial and real networks to verify efficiency and scalability of our algorithm. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/SSCI.2015.114 | 2015 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI) |
Keywords | Field | DocType |
genetics,indexes,statistics,sociology,linear programming | Data mining,Social network,Disjoint sets,Computer science,Popularity,Theoretical computer science,Linear programming,Genetic algorithm,Modularity,Scalability | Conference |
Citations | PageRank | References |
1 | 0.36 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| jaswant meena | 1 | 1 | 0.36 |
| V. Susheela Devi | 2 | 47 | 9.21 |