Anzeige
Erschienen in:
2006 | OriginalPaper | Buchkapitel
Robust Reputations for Peer-to-Peer Marketplaces
verfasst von : Jonathan Traupman, Robert Wilensky
Erschienen in: Trust Management
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
We have developed a suite of algorithms to address two problems confronting reputation systems for large peer-to-peer markets: data sparseness and inaccurate feedback. To mitigate the effect of inaccurate feedback – particularly retaliatory negative feedback – we propose EM-trust, which uses a latent variable statistical model of the feedback process. To handle sparse data, we propose Bayesian versions of both EM-trust and the well-known Percent Positive Feedback system. Using a marketplace simulator, we demonstrate that these algorithms provide more accurate reputations than standard Percent Positive Feedback.