It is the ultimate test for big data - finding the secret algorithm of love.
Online dating companies say they have the know-how and scientists have been studying the question for years.
The answers, alas, are not clear-cut for the lovelorn who scour the internet looking for the perfect mate.
A 2012 study by researchers led by Northwestern University psychologist Eli Finkel concluded there was no algorithm that could predict a successful match, notwithstanding the claims of online dating firms.
"No compelling evidence supports matching sites' claims that mathematical algorithms work," said the study published in the journal Psychological Science in the Public Interest.
The researchers wrote that dating sites "are in a poor position to know how the two partners will grow and mature over time ... and how the dynamics of their interaction will ultimately promote or undermine romantic attraction and long-term relationship well-being".
But could it be that dating sites simply have not yet found the right mathematical formula?
A team of researchers led by Kang Zhao at the University of Iowa say in the study they found a method that markedly improves chances for online matches.
The new formula, interestingly, is based on the techniques used by online companies such as Amazon and Netflix, and are based on user recommendations, not merely profiles filled out by love seekers.
"What we did in our study is to look at users' activity instead of their profiles," Zhao said. "Your activity reflects your tastes and your attractiveness, or … unattractiveness. We extend what Amazon and Netflix have been using."
So if person A shares a lot of characteristics with person B who draws a lot of positive responses from the opposite sex, the reasoning is that person A will elicit a similar response.
This is known as "collaborative filtering" and is used by online commerce firms, according to Zhao, who has been in talks with dating companies on using his formula. "The new model can better recommend partners that match a user's taste and attractiveness," said the study to appear later this year in the IEEE Intelligent Systems Journal with co-authors Xi Wang, Mo Yu, and Bo Gao.
He said that using this system, "the chances of getting a response increase 40 per cent" compared to a baseline without collaborative filtering.
"Whether it's a perfect match, I don't know," he said. "But we can at least help people get a successful date."