Name
Abstract | ||
|---|---|---|
The trust value between two nodes is important for their interactions in social network . In this paper we propose an ACO-based trust inference algorithm. First, we use the Ant Colony Optimization algorithm to find two trust trains with high trust value between any two nodes, since the most accurate information comes from the node with the highest trust value. We optimized the corresponding parameters of the ACO algorithm to make it adaptive to our problem. Indirect trust value between two nodes is calculated according to direct trust value and trust chains got by ACO. The statistical analysis indicates that our algorithm gains more accuracy of trust value computing compared with a classical trust algorithm. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/BWCCA.2014.70 | BWCCA |
Keywords | Field | DocType |
ant colony optimization algorithm,ant colony optimisation,social network,statistical analysis,aco-based trust inference algorithm,trusted computing,trust trains,trust value computing,indirect trust value,trust chains,social networking (online),classical trust algorithm,social trust,clustering algorithms,algorithm design and analysis,ant colony optimization,accuracy | Ant colony optimization algorithms,Algorithm design,Inference,Computer science,Algorithm,Artificial intelligence,Cluster analysis,Social trust,Statistical analysis | Conference |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
3 | ||