Name
Abstract | ||
|---|---|---|
We describe a new method of voting system in social networks environment1. We suggest a sequence of continuous support via a social network after electing representatives or exemplars in the network that is different from the typical majority voting. In other words, this paper suggests the method of elected representatives using network clustering approach to counts voting. On the network structure, sending messages from each node reflects the influence or importance to the representative and that can be readjusted and send back to each node. Where the representatives can be clustered within which the selectivity can be decided through the graph edges. In the experiment our algorithm outperformed conventional approaches in social network synthetic dataset as well as real dataset. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3102254.3102268 | WIMS |
Field | DocType | ISBN |
Network clustering,Data mining,Graph,Social network,Voting,Computer science,Artificial intelligence,Clustering coefficient,Majority rule,Cluster analysis,Machine learning,Network structure | Conference | 978-1-4503-5225-3 |
Citations | PageRank | References |
3 | 0.43 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rich C. Lee | 1 | 3 | 0.43 |
| Alfredo Cuzzocrea | 2 | 1751 | 200.90 |
| Wookey Lee | 3 | 196 | 29.22 |
| Carson K. Leung | 4 | 1625 | 115.64 |