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zTrust: Adaptive Decentralized Trust Model for Quality of Service Selection in Electronic Marketplaces
Author(s) -
Noorian Zeinab,
Marsh Stephen,
Fleming Michael
Publication year - 2016
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/coin.12055
Subject(s) - computer science , merge (version control) , procurement , service provider , crowdsourcing , trustworthiness , quality (philosophy) , probabilistic logic , selection (genetic algorithm) , service quality , service (business) , risk analysis (engineering) , artificial intelligence , computer security , business , marketing , world wide web , information retrieval , philosophy , epistemology
We present an adaptive decentralized trust formalization well suited for electronic commerce. Our model, called zTrust , constitutes two essential elements. The first is the adviser modeling mechanism that enables consumer agents to merge the cognitive and the probabilistic views of trust and adaptively calculate the trustworthiness of advisers according to environmental conditions, information availability, and participants' behavioral dispositions. Using this mechanism, consumers are able to form their social network consisting of the most reliable advisers. The second element is a trust‐oriented service selection framework that models the qualification and trustworthiness of providers in delivering the multiattribute products and adopts a procurement auction model to choose the most pertinent provider that meets a consumer's quality of service requirements. We give a formal description of our approach and validate it with simulations demonstrating that our solution yields high‐quality results under various realistic conditions. Experimental results indicate that the zTrust model can be effectively employed in dynamic agent‐oriented e‐commerce applications.