Name
Title | ||
|---|---|---|
Social network analysis-based conflict relationship investigation and conflict degree-based consensus reaching process for large scale decision making using sparse representation. |
Abstract | ||
|---|---|---|
•A social network and sparse representation-based conflict investigation process (S-CRIP) is presented.•The defineded opinion and behavior conflicts can be detected and classified exactly by S-CRIP.•A novel conflict degree-based consensus reaching process (CRP) is presented.•Conflict degree is used to check the consensus is reached or not in CRPs for LSDM events.•The large-scale decision making model can be used for any numerical evaluation environments. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.inffus.2019.02.004 | Information Fusion |
Keywords | Field | DocType |
Conflict relationship investigation,Conflict degree-based consensus reaching process,Social network analysis,Sparse representation,Large-scale decision making | Data science,Negative relationship,Group conflict,Public participation,Social network analysis,Sparse approximation,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
50 | 1566-2535 | 7 |
PageRank | References | Authors |
0.39 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ru-Xi Ding | 1 | 77 | 3.74 |
| Xueqing Wang | 2 | 119 | 6.45 |
| Kun Shang | 3 | 8 | 0.73 |
| Francisco Herrera | 4 | 27391 | 1168.49 |