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Click Me Maybe: Inside eHarmony's matchmaking machine

Click Me Maybe: Inside eHarmony's matchmaking machine

Dating site's tech chief Prateek Jain shares the machine learning secrets of the ‘brains behind the butterflies’

A user that more frequently clicks on blonde-haired user profiles will be served up with more blonde matches.

Preferences are also parsed from written profiles. “Some people mention ‘I have a thing for guys with beards’ right? If I see that in your profile and can detect in other people’s photos whether they have a beard we can use that as a criteria for matching,” Jain says.

Another match factor is a user’s site usage. For example, if a user is usually the one to send the first message, they are matched to people who are ‘shy’ users who rarely do.

“If you can match those people you can increase the chances of success. Not just for you but the shy individual as well,” Jain says.

As part of the image analysis, eHarmony is currently working on a tool to help users decide which photos to post on their profile and in which order. Its data has discovered, for example, that photos of individuals wearing sunglasses or in a group don’t do as well. By alerting users when they upload a photo like that, eHarmony will help them maximise the appeal of their profile, Jain says.

Occasionally, the site will serve up a match that is outside your usual preferences, called ‘Serendipitous Recommendations’. This helps users from ‘getting caught in a bubble’, Jain says.

Click me maybe

The front facing systems emit thousands of events. The events are pumped through Apache Kafka and onto Hadoop for processing. Server logs “to figure out where users are clicking” also go into Hadoop and the MapReduce system.

“We also have traditional data warehouse systems which interact with legacy Oracle systems. We keep historical data back to last 15 years or so,” Jain says.

Jain says most of the data sits on premise, however the company is mounting a cloud migration effort, and currently assessing different providers.

“We’ve realised that we cannot be sitting on sidelines as the industry moves to cloud. Running our own data centres has its own challenges, not just on capital but the time the engineering team is maintaining infrastructure and dealing with vendors and partners if something goes wrong,” Jain, who built eHarmony's spin-off job site Elevated Careers in AWS, says.

“For a business of our size I would rather have all my engineering energy focused on new products rather than infrastructure.”

In this area, eHarmony is playing catch up to its born-in-the-cloud rivals.

“They don’t have the baggage eHarmony has to maintain years of data. That’s what I’m trying to unshackle us from,” Jain adds.

It is hoped over the next year, the 100 string technology will ship product multiple times a day, rather than the current multiple times a week.

“The ultimate vision is: an engineer commits code, it gets picked up by the testing system, it auto runs test cases. If they look good it promotes the code to productions systems and makes it live. If you can cut down this development cycle you can learn your lessons much faster – rather than working on a feature for months, releasing it and realising people don’t like it,” Jain says.

An effort is also being made to make the enrolling process far easier on users. This could involve them offering their social media data for eharmony to learn about their likes and dislikes, rather than having to answer questions about them.

“Our barrier to entry is a bit high right now. We would like to be creative around – how do we ask you all the questions we ask you today and figure out a lot of that without having to ask you explicitly? What can we learn about your personality with some of your social data?” Jain says.


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Tags social mediaOracleGoogledata warehousebig datactohadoopartificial intelligenceAIeHarmonyAWSimage recognitionmachine learningdatingMLrecommendation engineKafka

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