The way the Match algorithm learns, he says, is similar to the way the human brain learns. “When you give it stimuli, it forms neural pathways,” he says. “If you stop liking something, those shut off. 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...
As a result, Match began “weighting” variables differently, according to how users behaved. For example, if conservative users were actually looking at profiles of liberals, the algorithm would learn from that and recommend more liberal users to them. Indeed, says Thombre, “the politics one is quite interesting. Conservatives are far more open to reaching out to someone with a different point of view than a liberal is.” That is, when it comes to looking for love, conservatives are more open-minded than liberals....
...By evaluating your stated preferences, mapping your site behaviour and using triangulation, Match.com will get to know you, and what you want, better than you know yourself.