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An Axiomatic Approach to Personalized Ranking Systems
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Dagstuhl Seminar Proceedings, Volume 7271
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2007-10-02
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Alon Altman and Moshe Tennenholtz. An Axiomatic Approach to Personalized Ranking Systems. In Computational Social Systems and the Internet. Dagstuhl Seminar Proceedings, Volume 7271, pp. 1-25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)
https://doi.org/10.4230/DagSemProc.07271.3
https://doi.org/10.4230/DagSemProc.07271.3
Abstract
Personalized ranking systems and trust systems are an
essential tool for collaboration in a multi-agent
environment. In these systems, trust relations between
many agents are aggregated to produce a personalized
trust rating of the agents. In this paper we introduce
the first extensive axiomatic study of this setting,
and explore a wide array of well-known and new
personalized ranking systems. We adapt several axioms
(basic criteria) from the literature on global ranking
systems to the context of personalized ranking systems,
and fully classify the set of systems that satisfy all
of these axioms. We further show that all these axioms
are necessary for this result.
Keywords
- Ranking systems
- trust
- axiomatization
- incentives
- mechanism design
- game theory
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