How the Web Reads Your Mind

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Winning the Netflix Prize

These techniques aren't rocket science—they're statistics based. To learn more about how latent factors are uncovered, Goldman recommended folks turn to the site operated by the recent winners of the Netflix recommendation prize. For laypersons, I can recommend Wired's story covering the race to win the Netflix prize, which shows how most of the people trying to improve recommendation engines are doing so in the open and piggybacking on each others' efforts—something Apple doesn't seem to be endorsing, given that Goldman's post was deleted.

As the devices on which we consume our information become smaller, the need for better recommendations has moved beyond a nicety for discovering long-tail content into a necessity for displaying optimal results quickly over a mobile connection and on a small screen. I discussed this problem a while back with Elizabeth Churchill, principal research scientist and manager of the Internet Experiences Group at Yahoo (YHOO), and she emphasized that tailored recommendations are important for mobile users, not only because the screen sizes are small, but also because mobile connections are slower and people don't have the patience to wait for a lot of results to load.

The ability to use cloud computing, to access huge amounts of data, and then to crunch that data to make recommendations and deliver them in a format fit for mobile consumption, will be the key stepping-stones for the next generation of the Web.

Other stories from the GigaOM Network:

The New Reality of the Twitter Ecosystem

Why Glee Is TV's Most Web Video-savvy Series (and Why It Isn't)

Comcast COO: We're Not Competing With Google TV

Chip University: Ten Execs from the Chip Biz Leading Greentech

What Can Web Workers Learn from Corporations?

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