A case-based reasoning framework to choose trust models for different E-marketplace environments
Irissappane, Athirai Aravazhi
Date of Issue2015
School of Computer Engineering
The performance of trust models highly depend on the characteristics of the environments where they are applied. Thus, it becomes challenging to choose a suitable trust model for a given e-marketplace environment, especially when ground truth about the agent (buyer and seller) behavior is unknown (called unknown environment). We propose a case-based reasoning framework to choose suitable trust models for unknown environments, based on the intuition that if a trust model performs well in one environment, it will do so in another similar environment. Firstly, we build a case base with a number of simulated environments (with known ground truth) along with the trust models most suitable for each of them. Given an unknown environment, case-based retrieval algorithms retrieve the most similar case(s), and the trust model of the most similar case(s) is chosen as the most suitable model for the unknown environment. Evaluation results confirm the effectiveness of our framework in choosing suitable trust models for different e-marketplace environments.
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Journal of artificial intelligence research
© 2015 AI Access Foundation. This paper was published in Journal of Artificial Intelligence Research and is made available as an electronic reprint (preprint) with permission of AI Access Foundation. The published version is available at: [http://dx.doi.org/10.1613/jair.4595]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.