Evaluation and Deployment of a People-to-People Recommender in Online Dating

Abstract

This paper reports on the successful deployment of a peopleto-people recommender system in 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 key metrics generally hold their value or show an increase compared to the trial results, and that the recommender system delivered its projected benefits.