Fair Reciprocal Recommendation in Matching Markets

Recommender systems play an increasingly crucial role in shaping people’s opportunities, particularly in online dating platforms. It is essential from the user’s perspective to increase the probability of matching with a suitable partner while ensuring an appropriate level of fairness in the matching opportunities.

Authors

Yoji Tomita (ORCID: https://orcid.org/0009-0007-6828-4424)
Tomohiko Yokoyama (ORCID: https://orcid.org/0009-0004-7641-029X)

Institutions

CyberAgent (Japan) (JP)
The University of Tokyo (JP)

Publication Details

Published: 2024-10-08
DOI: https://doi.org/10.1145/3640457.3688130
Citations: 2
Primary Topic: Game Theory and Voting Systems
Type: article
Field-Weighted Citation Impact: 2.26

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article

Fair Reciprocal Recommendation in Matching Markets

Yoji Tomita, Tomohiko Yokoyama

Oct 8, 2024

2 citations

Game Theory and Voting Systems

2.26

article

Fair Reciprocal Recommendation in Matching Markets

Yoji Tomita, Tomohiko Yokoyama

October 8, 2024article en

2 citations

Abstract

CyberAgent (Japan) (JP), The University of Tokyo (JP)

Openalex Percentile: Top 8%

Game Theory and Voting Systems

2.26

DOI Open Access PDF OpenAlex

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Fair Reciprocal Recommendation in Matching Markets — Yoji Tomita, Tomohiko Yokoyama · (2024) | TGRS Research Map | TGRS