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Integrating Indicators of Trustworthiness into Reputation-Based Trust Models

Abstract : Reputation-based trust models are essentially reinforcement learning mechanisms reliant on feedback. As such, they face a cold start problem when attempting to assess an unknown service partner. State-of-the-art models address this by incorporating dispositional knowledge, the derivation of which is not described regularly. We propose three mechanisms for integrating knowledge readily available in cyber-physical services (e.g., online ordering) to determine the trust disposition of consumers towards unknown services (and their providers). These reputation-building indicators of trustworthiness can serve as cues for trust-based decision making in eCommerce scenarios and drive the evolution of reputation-based trust models towards trust management systems.
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Sascha Hauke, Florian Volk, Sheikh Habib, Max Mühlhäuser. Integrating Indicators of Trustworthiness into Reputation-Based Trust Models. 6th International Conference on Trust Management (TM), May 2012, Surat, India. pp.158-173, ⟨10.1007/978-3-642-29852-3_11⟩. ⟨hal-01517646⟩

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