A Deployed People-to-People Recommender System in Online Dating
AbstractOnline 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.
How to Cite
Wobcke, W., Krzywicki, A., Kim, Y. S., Cai, X., Bain, M., Compton, P., & Mahidadia, A. (2015). A Deployed People-to-People Recommender System in Online Dating. AI Magazine, 36(3), 5-18. https://doi.org/10.1609/aimag.v36i3.2599
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