Abstract:
This work presents the design of a trust model to derive recommendation trust from heterogeneous agents. The model is a novel application of neural network in evaluating ...Show MoreMetadata
Abstract:
This work presents the design of a trust model to derive recommendation trust from heterogeneous agents. The model is a novel application of neural network in evaluating multiple recommendations of various trust standards with and without deceptions. The experimental results show that 97.22% estimation errors are less than 0.05. The results also show that the model has robust performance when there is high estimation accuracy requirement or when there are deceptive recommendations.
Published in: Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).
Date of Conference: 24-24 September 2004
Date Added to IEEE Xplore: 18 October 2004
Print ISBN:0-7695-2101-0
Contents 