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Summary:

Gravity, a startup that personalizes reader content for web publishers, is opening up its recommendation engine to anyone that wants to use it. Considering the increasing importance of personalization online, this could be a good deal.

A sample interest graph from Gravity.

Gravity, a Santa Monica, Calif-based startup that personalizes reader content for web publishers, is opening up its recommendation engine to anyone that wants to use it. If you don’t mind a few sponsored stories popping up in the newsfeed — a condition of using the free platform — this could be a pretty good deal.

Gravity’s recommendation system is based on its interest graph technology, which we detailed last year. Here’s how I described it then:

[T]he gist is that humans first serve as guides for machine-learning algorithms by determining connections between terms within large data sets, then the algorithms take over to complete the job faster than humans ever could. When they’re done, the humans step in one more time to kill any bad connections between terms. The result is a system that can determine with high accuracy that a person tweeting about Vanessa Laine (Los Angeles Laker Kobe Bryant’s ex-wife), for example, is probably more interested in basketball than about Laine’s date of birth or other accurate but irrelevant information.

As new content streams into Gravity’s system, it’s analyzed and categorized in real time, then presented to users accordingly based on their interests and behavioral history.

How Gravity's platform works

How Gravity’s platform works

Graph processing and graph databases — which store and analyze data based on their relationship to one another — are critical to our onlines lives, powering everything from online recommendations to social search to knowledge discovery. Graph technologies are also the focal point of some impressive life sciences work from companies such as Syapse and Ayasdi, which will be presenting at Structure: Data in New York next month.

But publishers struggling to stand out on a noisy web might have the most to gain from graphs and personalization, generally. At our PaidContent Live conference (April 17 in New York), executives from Prismatic, Zite and Bluefin Labs will take the stage to talk about the importance of personalization for helping consumers filter through the deluge of content online so they can find what they really want. It’s arguable that the trick to keeping readers happy is knowing what they want to read — possibly better than they do themselves.

According to Gravity, its platform currently “delivers more than 25 million personalized content recommendations per day to more than 200 million users. Beta partners have reported click through rates two to three times above previous levels, return visitation increases of 300 percent and session length increases up to 40 percent.”

  1. Is an internet filtered and personalized a good thing ?

    How will we any ideas/news/ that is relavant but outside of what the algorithm thinks is important to me ever be surface.

    The filter bubble speaks to many of these issues

    http://www.thefilterbubble.com/

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  2. This is a terrible idea.

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  3. I can see some benefit. I live in a reality distorting bubble as much as the next person. But not sure I need machine learning to amplify it. I wonder if these techniques rather than being used so advertisers can better manipulate me, could be used to help push the limits of my limited world. Oh my, I might or might not buy into that. Aye, there’s the rub.

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