McKinlay started by creating fake profiles on OkCupid, and writing programs to answer questions that had also been answered by compatible users — the only way to see their answers, and thus work out how the system matched users. McKinlay's operation was possible because OkCupid, and so many other sites like it, are much more than just simple social networks, where people post profiles, talk to their friends, and pick up new ones through common interest. We rely on advertising to help fund our award-winning journalism. He was contacted by Nick Tsinonis, the founder of a small UK dating site called yesnomayb, who asked him to see if his approach, called collaborative filtering, would work on people as well as films. Loading comments… Trouble loading? The researchers then fed the information into an algorithm to predict who would hit it off.
As a maths student, Tarr had some experience of computers, and although he couldn't program them himself, he was sure they could be used to further his primary interest:
Hinge employs new algorithm to find your ‘most compatible’ match
Nearly every Silicon Valley startup video features two photogenic young people being brought together, whatever the product, and the same matching algorithms are at work whether you're looking for love, a jobbing plumber, or a stock photograph. RecSys is already powering the recommendations for art discovery site ArtFinder, the similar articles search on research database Nature. All I needed to do was fill out some basic personal information. Collaborative filtering works by collecting the preferences of many people, and grouping them into sets of similar users. Anyone typing their requirements into such a device would receive "in seconds" the name of a compatible match who was also free that night.