Virtual interaction with strangers often makes use of underlying trust networks. Usually, existing proposals address the evaluation of global (unique) trust for a given node within the network. In this paper we discuss about how to assess the local (direct) trust a node receives from each of his neighbors. Our proposal is social-based and takes into account both positive and negative experiences as well as the history of past feedbacks, ensuring good stability also when a node receives hundreds of positive feedbacks briefly followed by few negative feedbacks. In order to highlight the stability of this approach we performed several simulations with different networks.
Titolo: | Social-based arcs weight assignment in trust networks |
Autori interni: | |
Data di pubblicazione: | 2016 |
Serie: | |
Abstract: | Virtual interaction with strangers often makes use of underlying trust networks. Usually, existing proposals address the evaluation of global (unique) trust for a given node within the network. In this paper we discuss about how to assess the local (direct) trust a node receives from each of his neighbors. Our proposal is social-based and takes into account both positive and negative experiences as well as the history of past feedbacks, ensuring good stability also when a node receives hundreds of positive feedbacks briefly followed by few negative feedbacks. In order to highlight the stability of this approach we performed several simulations with different networks. |
Handle: | http://hdl.handle.net/20.500.11769/73231 |
ISBN: | 978-3-319-25015-1 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |