An Axiomatic Approach to Personalized Ranking Systems
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.
@inproceedings{ijcai2007p192,
title = {An Axiomatic Approach to Personalized Ranking Systems},
author = {Altman, Alon and Tennenholtz, Moshe},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1187--1191},
year = {2007},
url = {https://ijcai.org/proceedings/2007/192},
}
TY - CPAPER TI - An Axiomatic Approach to Personalized Ranking Systems AU - Altman, Alon AU - Tennenholtz, Moshe T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1187 EP - 1191 UR - https://ijcai.org/proceedings/2007/192 ER -Copied
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