Feeds 2.0 and the Netflix Prize

I've blogged about my friends at Feeds 2.0 many times over the past few years; I've followed the Netflix prize out of interest since it was covered in Wired back in 2007, mainly because I was rooting for the Feeds 2.0 team...

For those of you who may not spend your weekends and evenings reading up on artificial intelligence, here's an overview of the Netflix competition:

Netflix released a large movie rating dataset and challenged the data mining, machine learning and computer science communities to develop systems that could beat the accuracy of their in-house developed recommendation system (Cinematch) by 10%. In order to render the challenge more interesting, the company will award a Grand Prize of $1M to the first team that will attain this goal, and in addition, Progress Prizes of $50K have been awarded on the anniversaries of the Prize to teams that have made sufficient accuracy improvements. Apart from the financial incentive however, the Netflix Prize contest is enormously useful for recommender system research since the released Netflix dataset is by far the largest ratings dataset ever becoming available to the research community. Most work on recommender systems outside of companies like Amazon or Netflix up to now has had to make do with the relatively small 1M ratings MovieLens data or the 3M ratings EachMovie dataset. Netflix provided 100480507 ratings (on a scale from 1 to 5 integral stars) along with their dates from 480189 randomly-chosen, anonymous subscribers on 17770 movie titles. The data were collected between October, 1998 and December, 2005 and reflect the distribution of all ratings received by Netflix during this period. Netflix withheld over 2M most recent ratings from those same subscribers over the same set of movies as a competition qualifying set and contestants are required to make predictions for all 2M withheld ratings in the qualifying set.

I was thrilled when I saw the final Leader Board: The Ensemble (Feeds 2.0 + others) was at the top:

The final winner will not be announced until next month; Netflix still has to decide which of the leading algorithms perform best and how they score on various tests...

So, as the latest Wired article says, it ain't over til it's over.

Good luck Nicholas!

Comments

[Nicholas]

Hi Jason,

Just found your post through Feeds 2.0 :)

Many thanks for the coverage!

Nicholas

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I was just going through searching for some information and i got your blog which is quite interesting so i manage to leave an appreciate comment.

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I am eagerly waiting to hear the finale winner of the contests...when finale results are going to be out.

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thanks for the coverage :) interesting write up thoug :)) xoxo..