FROM THE WEB: ‘How Online Dating is Improving Matching through Big Data’ – Thomas Levi of POF


The analytics and big data website KD Nuggets have interviewed Thomas Levi, the Senior Data Scientist at Plenty of Fish, about the site’s use of big data.

Levi has a doctorate in Theoretical Physics and String Theory from the University of Pennsylvania.

Levi explains the different ways the Canadian-based site uses big data both externally and internally – on successful couples to tailor matching algorithms, and for internal areas like scammer detection.

He also speaks of using Topic Modeling and LDA for “feature reduction” to improve their matching algorithms.

This helps to cluster and categorise text documents together in a way that humans would – such as putting skiing and snowboarding together.

Levi says:

“It can be used as the basis for a matching algorithm on its own, as a factor in some of our other matching algorithms, or as a way of showing similar users to one someone is viewing.

“I believe its strongest potential is in search, as we can allow our members to insert whatever they want their potential match to be interested in and show them thematic matches, e.g. typing in “skiing and Netflix” will get you matches interested in outdoor sports and  TV/movies. If your readers want to see it, they should let us (or me) know.”

Read the interview here.