The Fallacy of Endogenous Discounting of Trust Recommendations

Muller, Tim; Liu, Yang; Zhang, Jie

Abstract

Recommendations are widely used in recommender systems, reputation systems, and trust-based security systems. Some existing reputation systems and trust-based security systems use the flawed notion of endogenous discounting. Endogenous discounting is the idea that claims deviating from prior expectations should be ignored or discounted, which introduces confirmation bias. To show the fallacy of endogenous discounting, we construct a semantic meta-model that captures the key notions surrounding recommendations. We prove that any model covered by the meta-model can be formulated in a divide-and-conquer fashion. We show how divide-and-conquer clashes with endogenous discounting. Lastly, we discuss the implications on existing work that applies endogenous discounting, and provide suggestions for future work.

Citation

Muller, T., Liu, Y., & Zhang, J. (2015, May). The Fallacy of Endogenous Discounting of Trust Recommendations. Presented at 2015 International Conference on Autonomous Agents and Multiagent Systems, Istanbul, Turkey

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2015 International Conference on Autonomous Agents and Multiagent Systems
• Start Date: May 4, 2015
• End Date: May 8, 2015
• Acceptance Date: Nov 28, 2014
• Publication Date: 2015
• Deposit Date: Jan 13, 2020
• Pages: 563-572
• Book Title: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems
• ISBN: 978-1-4503-3413-6
• DOI: https://doi.org/10.5555/2772879.2772951
• Public URL: https://nottingham-repository.worktribe.com/output/2142170
• Publisher URL: https://dl.acm.org/doi/10.5555/2772879.2772951