Trust Is Much More than Subjective Probability: Mental Components and Sources of Trust
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 6 - Volume 6
Bayesian Network-Based Trust Model
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Running up the bid: detecting, predicting, and preventing reserve price shilling in online auctions
ICEC '03 Proceedings of the 5th international conference on Electronic commerce
Efficient, Self-Contained Handling of Identity in Peer-to-Peer Systems
IEEE Transactions on Knowledge and Data Engineering
Computing trust from revision history
Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services
Controversial users demand local trust metrics: an experimental study on Epinions.com community
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Extracting trust from domain analysis: a case study on the wikipedia project
ATC'06 Proceedings of the Third international conference on Autonomic and Trusted Computing
Trust, untrust, distrust and mistrust – an exploration of the dark(er) side
iTrust'05 Proceedings of the Third international conference on Trust Management
Partners selection in multi-agent systems by using linear and non-linear approaches
Transactions on computational science I
Combining statistics and arguments to compute trust
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Trust and matching algorithms for selecting suitable agents
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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1. This paper proposes a generic method for identifying elements in a domain that can be used as trust evidences. As an alternative to external infrastructured approaches based on certificates or user recommendations we propose a computation based on evidences gathered directly from application elements that have been recognized to have a trust meaning. However, when the selection of evidences is done using a dedicated infrastructure or user's collaboration it remains a well-bounded problem. Instead, when evidences must be selected directly from domain activity selection is generally unsystematic and subjective, typically resulting in an unbounded problem. To address these issues, our paper proposes a general methodology for selecting trust evidences among elements of the domain under analysis. The method uses presumptive reasoning combined with a human-based and intuitive notion of Trust. Using the method the problem of evidence selection becomes the critical analysis of identified evidences plausibility against the situation and their logical consistency. We present an evaluation, in the context of the Wikipedia project, in which trust predictions based on evidences identified by our method are compared to a computation based on domain-specific expertise.