A Deployed People-to-People Recommender System in Online Dating

  • Wayne Wobcke University of New South Wales
  • Alfred Krzywicki University of New South Wales
  • Yang Sok Kim Keimyung University
  • Xiongcai Cai University of New South Wales
  • Michael Bain University of New South Wales
  • Paul Compton University of New South Wales
  • Ashesh Mahidadia smartAcademic


Online dating is a prime application area for recommender systems, as users face an abundance of choice, must act on limited information, and are participating in a competitive matching market. This article reports on the successful deployment of a people-to-people recommender system on a large commercial online dating site. The deployment was the result of thorough evaluation and an online trial of a number of methods, including profile-based, collaborative filtering and hybrid algorithms. Results taken a few months after deployment show that the recommender system delivered its projected benefits.