Online dating arises as a popular venue for finding romantic partners in recent years. Many online dating sites adopt recommender systems to help their users. However, few of current research provides solutions to cold start problem, i.e., providing recommendations to new users. In this research, we propose a new approach of providing reciprocal online dating recommendations to new users. Specifically, we detect communities from existing users, match new users to these communities, and take advantage of reciprocal activities of those community members to provide recommendations to new users. Using data from a popular U.S. online dating site, experiments show that our approach greatly outperforms existing methods.
['Mo Yu', 'Xiaolong Zhang', 'Derek A. Kreager']
New to online dating? Learning from experienced users for a successful match