For McKinlay’s plan to work, he’d have to find a pattern in the survey data—a way to roughly group the women according to their similarities. The breakthrough came when he coded up a modified Bell Labs algorithm called K-Modes. First used in 1998 to analyze diseased soybean crops, it takes categorical data and clumps it like the colored wax swimming in a Lava Lamp. With some fine-tuning he could adjust the viscosity of the results, thinning it into a slick or coagulating it into a single, solid glob. He played with the dial and found a natural resting point where the 20,000 women clumped into seven statistically distinct clusters based on their questions and answers. “I was ecstatic,” he says. “That was the high point of June.” […] Most unsuccessful daters confront self-esteem issues. For McKinlay it was worse. He had to question his calculations. […] “I think that what I did is just a slightly more algorithmic, large-scale, and machine-learning-based version of what everyone does on the site,” McKinlay says. Everyone tries to create an optimal profile—he just had the data to engineer one.
I’m not sure if I should be awestruck or creeped out.
The most enjoyable part of this story is that for all the advantages McKinlay has over most daters thanks to his math prowess, once it gets to the point of live interaction with another human he is back on equal footing.