Group recommendations: Axioms, impossibilities, and random walks

Omer Lev, Moshe Tennenholtz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We introduce an axiomatic approach to group recommendations, in line of previous work on the axiomatic treatment of trust-based recommendation systems, ranking systems, and other foundational work on the axiomatic approach to internet mechanisms in social choice settings. In group recommendations we wish to recommend to a group of agents, consisting of both opinionated and undecided members, a joint choice that would be acceptable to them. Such a system has many applications, such as choosing a movie or a restaurant to go to with a group of friends, recommending games for online game players, & other communal activities. Our method utilizes a given social graph to extract information on the undecided, relying on the agents influencing them. We first show that a set of fairly natural desired requirements (a.k.a axioms) leads to an impossibility, rendering mutual satisfaction of them unreachable. However, we also show a modified set of axioms that fully axiomatize a group variant of the random-walk recommendation system, expanding a previous result from the individual recommendation case.

Original languageEnglish GB
Title of host publication16th conference on Theoretical Aspects of Rationality and Knowledge (TARK 2017), July 2017, Liverpool, United Kingdom
Pages382-397
Volume251
DOIs
StatePublished - 25 Jul 2017
Event16th Conference on Theoretical Aspects of Rationality and Knowledge, TARK 2017 - Liverpool, United Kingdom
Duration: 24 Jul 201726 Jul 2017

Publication series

NameElectronic Proceedings in Theoretical Computer Science, EPTCS
PublisherOpen Publishing Association
ISSN (Print)2075-2180

Conference

Conference16th Conference on Theoretical Aspects of Rationality and Knowledge, TARK 2017
Country/TerritoryUnited Kingdom
CityLiverpool
Period24/07/1726/07/17

ASJC Scopus subject areas

  • Software

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