Name
Abstract | ||
|---|---|---|
In many real-world networks, a node often belongs to multiple communities. Therefore, overlapping community detection is an important task in social network analysis. CDFR is an efficient algorithm recently proposed for non-overlapping community detection. In this paper, CDFR is extended for overlapping community detection, and the extended algorithm is called as OCDFR. In OCDFR, CDFR is first called to obtain a non-overlapping community partition. Then, find the kth NGC (k=1, 2, 3,...) node for each node, and record the fuzzy relations between them. Based on the fuzzy relation between a node and its kth NGC, five decision methods are proposed to determine whether it can join the communities to which its kth NGC belongs. Experimental results on real-world networks and synthetic networks demonstrate that OCDFR is effective and highly competitive. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICDIS.2018.00040 | 2018 1st International Conference on Data Intelligence and Security (ICDIS) |
Keywords | DocType | ISBN |
Social network,overlapping community detection,fuzzy relation | Conference | 978-1-5386-5763-8 |
Citations | PageRank | References |
1 | 0.36 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nannan Lu | 1 | 14 | 6.24 |
| Wenjian Luo | 2 | 356 | 40.95 |
| Li Ni | 3 | 9 | 2.64 |
| hao jiang | 4 | 59 | 17.96 |
| Weiping Ding | 5 | 278 | 44.96 |