Optimizing Advisor Network Size in a Personalized Trust-Modelling Framework for Multi-agent Systems

Abstract. This paper explores potential improvements to Zhang’s personalized trust approach for e-commerce, in particular examining means of optimizing the number of advisors that each buyer maintains in their social network. We propose three such improvements, two directly relating to the size of the network (through either the use of a threshold or by setting a maximum network size), and a third which may indirectly reduce the necessary size by ensuring that relevant trust information from users outside this network remains available. We provide examples to illustrate these approaches, and propose future work to optimize certain aspects of these methods and evaluate their overall effectiveness.

• Type: Conference
• Year: 2010
• Where: AI
• Authors: Joshua Gorner
• Keywords: AI 2010, Artificial Intelligence, Maximum Network Size, Particular Examining Means, Zhang’s Personalized Trust