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An Axiomatic Approach to Personalized Ranking Systems

Authors Alon Altman, Moshe Tennenholtz



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Alon Altman
Moshe Tennenholtz

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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

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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