# Matching Theory-based Recommender Systems in Online Dating

arXiv: https://arxiv.org/abs/2208.11384 · HTML: https://mlsanity.com/paper/2208.11384/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2022.

## Built on by (most cited first, 4 of 4)

- [Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method](https://mlsanity.com/paper/2408.09748/) (2024)
- [Recommender Systems for Sustainability: Overview and Research Issues](https://mlsanity.com/paper/2412.03620/) (2024)
- [Off-Policy Evaluation and Learning for Matching Markets](https://mlsanity.com/paper/2507.13608/) (2025)
- [CUPID: A Real-Time Session-Based Reciprocal Recommendation System for a One-on-One Social Discovery Platform](https://mlsanity.com/paper/2410.18087/) (2024)

## Abstract (arXiv)

Online dating platforms provide people with the opportunity to find a partner. Recommender systems in online dating platforms suggest one side of users to the other side of users. We discuss the potential interactions between reciprocal recommender systems (RRSs) and matching theory. We present our ongoing project to deploy a matching theory-based recommender system (MTRS) in a real-world online dating platform.