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And once at Match, he, Ginsberg and a team of nine maths whizzes hired by Thombre, set about updating the Match algorithm.
After becoming executive vice-president and general manager of Match's North American operations in 2008, Ginsberg initially looked to her old employer, i2, for assistance."When you give it stimuli, it forms neural pathways," he says. It's learning as you go." The same principles are powering the recommendation engines at popular sites around the web.Amazon uses similar technology to recommend new products for people to buy, Pandora learns from likes and dislikes to customise its internet radio stations, and Netflix famously offered $1m to anyone who could improve the effectiveness of its algorithm by 10 per cent.Central to this effort has been the development, over the past two years, of an improved matchmaking algorithm. "If you say you want a guy between 30 and 35 in New York who has a master's degree, you're going to get thousands of matches."Codenamed "Synapse", the Match algorithm uses a variety of factors to suggest possible mates.While taking into account a user's stated preferences, such as desired age range, hair colour and body type, it also learns from their actions on the site.You meet her criteria, and she meets yours, so you're a good match," Thombre explained.
"But when we researched the data the whole idea of dissonance came into focus.
We sat in a conference room overlooking a floor full of computer engineers gazing at their monitors, and with a Power Point presentation, she endeavoured to show me how Match uses cutting-edge technology to cultivate age-old emotions.
With the number of paying subscribers using Match approaching 1.8 million, the company has had to develop ever more sophisticated programs to manage, sort and pair the world's singles.
Coloured lights flash from the ceilings, workers lounge on circular banquettes, dance music plays from hidden speakers.
Despite being in a mid-rise office tower overlooking a turnpike in the dry, landlocked city of Dallas, Texas, the Match offices are evocative of a racier environment, where anything might happen.
"We don't know ourselves very well on a descriptive level."The same is true for the millions of Match users, says Ginsberg, and she tried to incorporate dissonance into the algorithm.