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A social matching system for an online dating network

The proposed system has been evaluated on a dataset obtained from an online dating website.

Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).

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Online dating networks, a type of social network, are gaining popularity.Most services also encourage members to add photos or videos to their profile.Once a profile has been created, members can view the profiles of other members of the service, using the visible profile information to decide whether or not to initiate contact.The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks.This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches.Online dating (or Internet dating) is a system that enables strangers to find and introduce themselves to new personal connections over the Internet, usually with the goal of developing personal, romantic, or sexual relationships.An online dating service is a company that provides specific mechanisms (generally websites or applications) for online dating through the use of Internet-connected personal computers or mobile devices.Simply swipe right ("ja") if someone takes your fancy or left for no ("nej").They can only strike up a conversation with you if you’ve both swiped right – so you won’t get unwanted messages from strangers.Data from a live online dating network is used in evaluation.The success rate of recommendation obtained using the proposed method is compared with baseline success rate of the network and the performance is improved by double.

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