SoCal CTO

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Match Algorithm and Inputs

SoCal CTO

One of the common questions that I commonly get is: Tony, what inputs should we use as the basis for our matching algorithm? The people asking the above question don’t have that research and they also don’t really know how the matches should occur. How should the resulting algorithm use those inputs to form matches?

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Matching

SoCal CTO

I guess it was bound to happen, I now seem to be writing a series of posts around Matching. This is where I’ll keep my list of these posts, related articles and posts from other sources: Social Media Matching – Looks at how in many ways, everything is matching. Social Filtering – Content matching based on social signals.

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Matching Algorithm

SoCal CTO

Because I was the Acting CTO for eHarmony at it's start, I quite often get introduced to people who have an idea for a startup company that is based on some kind of matching algorithm. Each of these startup ideas has at it's core a matching algorithm that reduces the friction between a consumer and some need.

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Social Media Matching

SoCal CTO

Everything is Matching The real promise comes about as we get better tools for navigating all of this. If you know me - which you might not because you only have a thin relationship :) – you know that I’m going to say that a lot of this comes back to Matching Algorithms. Some days I start to feel that everything is matching.

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Match Performance Support

SoCal CTO

I’ve had several recent conversations with startups who are building companies based on matching. One of the things that I think gets commonly missed by these companies when I first talk to them is that they need more than providing matching, they need performance support. What do I mean by this?

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Startup CTO Speaking

SoCal CTO

Matching for Startups Having been involved in eHarmony from the start, Tony has naturally consulted with startups who are making matching a core aspect of their product including matching for social networks, careers, clothes, jobs, projects, college, tutoring services, doctors, service companies, investments, and many more.

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StartupRoar Adds Personalized Subscriptions

SoCal CTO

The system then can combine three pieces of information to figure out what will be most interesting to you: Social signal score – are people in the audience finding it interesting Topic match – does it match up with your interests Like sharing – are individuals who are like you sharing this The system uses these to both rank things on the site and (..)

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