Name
Abstract | ||
|---|---|---|
The participation to virtual contexts has been increased during the last decade. Trust is often used in such a scenario as a mechanism to establish reliable relationships. In addition, trust is often used to rank nodes in a network and the higher the rank the more preferred that node will be, therefore each node aims at getting a better position. Since a proper trade-off between the desired position and the related cost should be achieved, in this paper we analyse the rank-vs-cost function in trust networks, considering different topologies and different number of nodes. Results show that if we look for the first position (best rank), the effort is independent on network size for all topologies but scale-free, where costs increases strongly. Moreover, if we accept to achieve a good position, i.e., within the first 5% or 10% of nodes, all networks exhibit similar behaviour for any sizes. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1504/IJBIC.2017.085899 | INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION |
Keywords | Field | DocType |
trust, complex network, scale-free networks, random networks, ranking, reputation systems, recommendation systems, trust metrics, collaborative filtering, security | Network size,Recommender system,Collaborative filtering,Ranking,Network topology,Scale-free network,Complex network,Mathematics,Distributed computing | Journal |
Volume | Issue | ISSN |
10 | 2 | 1758-0366 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincenza Carchiolo | 1 | 261 | 51.62 |
| Alessandro Longheu | 2 | 142 | 29.98 |
| Michele Malgeri | 3 | 219 | 42.79 |
| Giuseppe Mangioni | 4 | 199 | 37.16 |