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A typical recommender setting is based online dating recommender systems on two kinds of relations similarity between users or between objects and the taste of users towards certain objects
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Recommender systems show a great potential for online dating where they could improve the value of the service to users and improve monetization of the service
Email Print. INTR ODUCTION Recommender systems t ypically co me in t w o a v ors users receiv e recommendations for ob jects or they receive recom-
In environments such as online dating websites, these two relations are difficult to separate, as the users can be similar to each other, but also have preferences towards other users, rate other users
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Recommender systems show a great potential for online dating where they could improve the value of the service to users and improve monetization of the service
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