Name
Title | ||
|---|---|---|
An Ant-Based Algorithm with Local Optimization for Community Detection in Large-Scale Networks |
Abstract | ||
|---|---|---|
In this paper, we propose a multi-layer ant-based algorithm (MABA), which detects communities from networks by means of locally optimizing modularity using individual ants. The basic version of MABA, namely SABA, combines a self-avoiding label propagation technique with a simulated annealing strategy for ant diffusion in networks. Once the communities are found by SABA, this method can be reapplied to a higher level network where each obtained community is regarded as a new vertex. The aforementioned process is repeated iteratively, and this corresponds to MABA. Thanks to the intrinsic multi-level nature of our algorithm, it possesses the potential ability to unfold multi-scale hierarchical structures. Furthermore, MABA has the ability that mitigates the resolution limit of modularity. The proposed MABA has been evaluated on both computer-generated benchmarks and widely used real-world networks, and has been compared with a set of competitive algorithms. Experimental results demonstrate that MABA is both effective and efficient (in near linear time with respect to the size of network) for discovering communities. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1142/S0219525912500361 | ADVANCES IN COMPLEX SYSTEMS |
Keywords | DocType | Volume |
Complex networks,community detection,ant-based algorithm,simulated annealing,modularity | Journal | 15 |
Issue | ISSN | Citations |
8 | 0219-5259 | 3 |
PageRank | References | Authors |
0.50 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dongxiao He | 1 | 201 | 28.10 |
| Jie Liu | 2 | 199 | 22.56 |
| Bo Yang | 3 | 822 | 64.08 |
| Yuxiao Huang | 4 | 10 | 2.25 |
| Dayou Liu | 5 | 814 | 68.17 |
| Di Jin | 6 | 317 | 49.25 |