Close but no Cigar for Netflix Recommender System

Ponca City, We Love You writes "In October 2006, Netflix, the online movie rental service, announced that it would award $1 million to the first team to improve the accuracy of Netflix's movie recommendations by 10% based on personal preferences. Each contestant was given a set of data from which three million predictions were made about how certain users rated certain movies and Netflix compared that list with the actual ratings and generated a score for each team. More than 27,000 contestants from 161 countries submitted their entries and some got close, but not close enough. Today Netflix announced that it is awarding an annual progress prize of $50,000 to a group of researchers at AT&T Labs, who improved the current recommendation system by 8.43 percent but the $1 million grand prize is still up for grabs and a $50,000 progress prize will be awarded every year until the 10 percent goal is met. As part of the rules of the competition, the team was required to disclose their solution publicly. (pdf)"

Comments

I'd say...

[Otter]

If the people who created Netflix's system are still with the company, I'd say they deserve some retroactive recognition (and bonuses). That's pretty damn good optimization if it's that hard to improve upon, and there seem to have been some really sophisticated people trying to beat them.

Re:I'd say...

[Potatomasher]

The idea is that with enough data, you could extract the "why" automatically. For example, if you rated all Arnold Scwarzenegger 5, then its probably because you like Arnold. If however you gave a rating of 1 to Kindergarden Cop, as well as "The Game Plan" and a bunch of similar movies, the system could also infer, that as much as you like Arnold, you don't like kids movies starring washed up "action" movie stars.

This is the whole idea behind the field of "machine learning": inferring causes/relationship/structure from raw data.

Is this feasible ? Maybe, maybe not. Is this easy ? Definitly not.
But then again if it was, they wouldn't put a 10$ Million prize tag on it.

Re:AT&T Labs?

[Anonymous Coward]

AT&T Labs = bunch of people from former Bell Labs = welfare for AI researchers ;)

like trying to win the lottery

[bzipitidoo]

I'm skeptical about these sorts of prizes. The X prize, Top Coder, Clay Institute Millennium Prizes-- if those were the only reasons to do something, few would. Seems pretty risky to do a lot of work for what amounts to a lottery ticket. So, who got 2nd place, and how well did they do? 1 group wins a paltry $50K and a little publicity and recognition, maybe even an endorsement or two, and the other 27000 plus get what? Nothing much. It's cool and fun to work on such problems, but people have bills to pay. Nice to have the sort of job where one gets paid to work on stuff like that. Any contestants reading this? Maybe you could enlighten the rest of us on why you bothered competing?

As for Netflix, I wonder how much such an improvement is worth to them? More than $50K, I imagine. Pardon my cynicism, but seems like contests like this are a way to get a lot of ideas and work for very little money.

Re:like trying to win the lottery

[MBCook]

Two reasons I can think of. One is the challenge. I like to code but I'm not great with coming up with projects to do myself. This kind of thing would be nice for that.

The other is the experience. If you get second in this, no, you won't win the prize. But you can bet that having that on your resume would make getting many jobs much easier. Amazon would like your skills. So would many other retailers.

Also, as a side note, it's not a lottery. There is a three prong legal test in the US to determine if something is a lottery. I think the three parts are you have to pay to get it, everyone has an equal chance of winning, and there is no skill involved. I'm not positive about the second part. This is free to enter and is based quite a bit on skill, so it's not like a lottery.

Don't exaggerate.

This isn't a way to get free work. It's a way to get very smart job candidates to find you. It's a recruiting tool. You don't honestly think that they will take the winning idea, pay the $1m, and then just say "bye" do you? They will offer that person a job if at all reasonable (if it's a team of 500 students, obviously they couldn't).

Re:like trying to win the lottery

[AdamTrace]

"Any contestants reading this? Maybe you could enlighten the rest of us on why you bothered competing?"

There are two immediate reasons I can think of why anyone would bother competing:

1) To win money.
2) Because they enjoy the challenge of trying to solve an interesting problem.

I'm just a simple coder, and knew that I didn't have any realistic chance of winning money. But I still found it very satisfying to try to come up with a solution and send it in and see how I did. I don't regret spending hours of my own leisure time on the project.

That said, eventually I gave it up. It was very clear that I'm not smart enough to meet the challenge. I had my fun, and it was time to move on to the next project. In summary, I don't think it's safe to assume that everyone is in it for the money.

"Pardon my cynicism, but seems like contests like this are a way to get a lot of ideas and work for very little money."

I call it "brilliant". Netflix probably put some pricetag on what it would pay to get >10% improvement on their system. That pricetag is probably more than $1 million. That means profit!

Here's an idea...

[the JoshMeister]

Why not give users more control over their recommendations? Heck, even a bunch of checkboxes would be useful.

For example, Netflix frequently recommends rated R movies to my family, but we have never rented a single R-rated movie and have no desire to do so. Moreover, every time we get a recommendation for an R-rated movie, we rate it "Not Interested." I've probably marked dozens of R-rated movies "Not Interested," but they continue to be recommended. (Either Netflix is trying to tell me to just give in and rent one already, or they really don't understand my family's movie preferences.)

A simple checkbox for "Do not recommend R-rated movies" would be all Netflix needs to substantially improve its accuracy for my family. I imagine Netflix could add checkboxes for similar criteria as well. In any case, I think a key point is giving more control over recommendations to the users themselves.