Not just a wink and smile: an analysis of user-defined success in online dating
Proceedings of the 2012 iConference
Predicting new user's behavior in online dating systems
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
Impression management through communication in online dating
Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing
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Due to the change in attitudes and lifestyles, people expect to find new partners and friends via various ways now-a-days. Online dating networks create a network for people to meet each other and allow making contact with different objectives of developing a personal, romantic or sexual relationship. Due to the higher expectation of users, online matching companies are trying to adopt recommender systems. However, the existing recommendation techniques such as content-based, collaborative filtering or hybrid techniques focus on users explicit contact behaviors but ignore the implicit relationship among users in the network. This paper proposes a social matching system that uses past relations and user similarities in finding potential matches. The proposed system is evaluated on the dataset collected from an online dating network. Empirical analysis shows that the recommendation success rate has increased to 31% as compared to the baseline success rate of 19%.