Reciprocal recommender system for online dating

19-Jan-2020 16:27

Moreover, they may also be the subject of intense interest from existing users now that their profile is public (often a site will heavily promote newly joined users).

The Decision Support and Recommender Systems (DSRS) research group was founded in mid-2018 by researchers in the School of Computer Science, Electrical and Electronic Engineering, and Engineering Maths (SCEEM), University of Bristol.

Thus a people-to-people recommender system needs to take into account the preferences of proposed candidates, who determine whether an interaction is successful, in addition to those of the user.

People-to-people recommenders are thus reciprocal recommenders (Pizzato et al. Or, putting this from the point of view of the user, a people-to-people recommender system must take into account both a user's taste (whom they find attractive) and their own attractiveness, so the presented candidates will find them attractive in return, and give a positive reply (Cai et al. Using online dating sites can be difficult for many people.

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The results show that our recommendation algorithms significantly outperform previously proposed approaches, and the collaborative filtering-based algorithms achieve much better performance than content-based algorithms in both precision and recall.Fourth, as is well known, dating is a type of market, a matching market, where people compete for scarce resources (partners) and are, in turn, a resource sought by others--see the recent user perspective of a labor market economist on the dating market that explores this idea in depth (Oyer 2014).

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