License
when quoting this document, please refer to the following
URN: urn:nbn:de:0030-drops-11527
URL: http://drops.dagstuhl.de/opus/volltexte/2007/1152/
Altman, Alon ; Tennenholtz, Moshe

An Axiomatic Approach to Personalized Ranking Systems

pdf-format:
Dokument 1.pdf (248 KB)

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.

BibTeX - Entry

@InProceedings{altman_et_al:DSP:2007:1152,
  author =	{Alon Altman and Moshe Tennenholtz},
  title =	{An Axiomatic Approach to Personalized Ranking Systems},
  booktitle =	{Computational Social Systems and the Internet},
  year =	{2007},
  editor =	{Peter Cramton and Rudolf M{\"u}ller and Eva Tardos and Moshe Tennenholtz },
  number =	{07271},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Internationales Begegnungs- und Forschungszentrum f{\"u}r Informatik (IBFI), Schloss Dagstuhl, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2007/1152},
  annote =	{Keywords: Ranking systems, trust, axiomatization, incentives, mechanism design, game theory}
}

Keywords: Ranking systems, trust, axiomatization, incentives, mechanism design, game theory
Seminar: 07271 - Computational Social Systems and the Internet
Documenttype: InProceedings
Issue date: 2007
Date of publication: 02.10.2007

DROPS-Home | Fulltext Search | Imprint Published by LZI