---
title: "An Axiomatic Approach to Personalized Ranking Systems"
authors:
  - "Alon Altman"
  - "Moshe Tennenholtz"
doi: ""
url: "https://ijcai.org/proceedings/2007/192"
pdf: "https://ijcai.org/proceedings/2007/0192.pdf"
venue: "Proceedings of the Twentieth International Joint Conference on Artificial Intelligence"
year: 2007
pages: "1187-1191"
track: ""
keywords:
---

# An Axiomatic Approach to Personalized Ranking Systems

Alon Altman, Moshe Tennenholtz

*Proceedings of the Twentieth International Joint Conference on Artificial Intelligence*, pages 1187-1191.

## 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 prove strong properties implied by the combination of these axioms.