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Build a Better Netflix, Win a Million Dollars?
Posted by
CmdrTaco
on Mon Oct 02, 2006 09:56 AM
from the trumps-our-redesign-contest dept.
from the trumps-our-redesign-contest dept.
An anonymous reader writes "In a quest to better movie recommendations, Netflix is opening their database (nytimes, registration and first child required) to users to try to craft a better recommendation technology. The problem is not easy. Says one researcher: 'You're competing with 15 years of really smart people banging away at the problem.'" Recommender systems are really an interesting problem, and that is likely very interesting data to play with.
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Netflix Prize Competitor Already Beats Netflix 174 comments
Baldrson writes "Within the first week of the announcement of The Netflix Prize a team has already beaten Netflix's own movie recommendation algorithm. This is pretty impressive given the previously quoted researcher who said: 'You're competing with 15 years of really smart people banging away at the problem.' The team is WXYZConsulting.com apparently registered by a data mining professor named Yi Zhang. Congratulations are in order for Netflix and Prof. Zhang's team who are demonstrating, yet again, the power of prizes to accelerate progress."
[+]
Netflix Now Offers Instant Online Movie Streaming 247 comments
An anonymous reader writes "If you're the owner of a video rental store, it may be time to start thinking about getting into a different business, according to ZDNet. Netflix, the online movie rental service, is offering a new feature that allows its subscribers to instantly view movies and TV shows on their PC. From the article: 'Following a one-time, under-60-second installation of a simple browser applet, most subscribers' movie selections will begin playing in their Web browser in as little as 10 to 15 seconds. Movies can be paused and a position bar gives viewers the ability to immediately jump to any point in the movie. In all, the instant watching feature requires only Internet connectivity with a minimum of one megabit per second of bandwidth.' These movies are in addition to the standard DVDs you can have at home, it should be pointed out. You can see a demonstration of the service at the Hacking Netflix blog." Only a small percentage of customers have it available at the moment, but they hope to roll it out to everyone within six months.
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Developers: Psychologist Beating Math Nerds in Race to Netflix Prize 205 comments
s1d writes "An almost-anonymous British psychologist named Gavin Potter has suddenly risen to the top of the Netflix prize charts. With his very first attempt, he got a score which took the BellKor team seven months to reach. Currently at a score of 8.07, he has only five teams ahead of him now in the race for the ultimate Netflix algorithm. 'Potter says his anonymity is mostly accidental. He started that way and didn't come out into the open until after Wired found him. "I guess I didn't think it was worth putting up a link until I had got somewhere," he says, adding that he'd been seriously posting under the name of his venture capital and consulting firm, Mathematical Capital, for two months before launching "Just a guy." When he started competing, he posted to his blog: "Decided to take the Netflix Prize seriously. Looks kind of fun. Not sure where I will get to as I am not an academic or a mathematician. However, being an unemployed psychologist I do have a bit of time."'"
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Science: Interest Still High In the Netflix Algorithm Competition 77 comments
circletimessquare brings us an update to the status of the million-dollar Netflix competition to develop a better algorithm for movie recommendations. We've discussed aspects of the competition since it started two years ago, but the New York Times has a lengthy overview of where it stands now.
"The Netflix competition is still going strong, with a vibrant, competitive roster of some 30,000 programmers around the globe hard at work trying to win the prize. The Times provides a look at some of the more obsessive searchers, such as Len Bertoni, a semi-retired computer scientist near Pittsburgh who logs 20 hours a week on the problem, oftentimes with the help of his children. There's also Martin Chabbert in Montreal: 'After the kids are asleep and I've packed the lunches for school, I come down at 9 in the evening and work until 11 or 12.' The article gets into the history of the search algorithm Netflix currently uses, and explores the hot commodity called 'singular value decomposition' that serves as the basis for most of the algorithms in competition."
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Seems like a free gift for Netflix to me... (Score:3, Insightful)
But if someone does win within a year they will still have the ability to use others' code, free of charge, as part of their product.
The article doesn't say but how will you know if your code is making choices better than their existing system? I wouldn't be submitting my code unless I was sure I was going to win. Then again I'm not a gambler or a coder
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But that seems pretty reasonable...you only have to hand over your code if you win, otherwise you're only submitting the results of yo
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Challenge Accepted (Score:2)
So, we can then conclude (Score:4, Funny)
So, the professionals have been working at it for a long time. Is it safe to assume some teenage to early college hacker will find a success within two weeks.
Simple (Score:5, Funny)
recomendation=MovieGenre.PORN;
else
recomendation=MovieGenre.CHICKFLICK;
And of course, slashdot must have sensed my post as my image word is "pervert"
Re:Simple (Score:5, Funny)
Old Version:
if(user.getGender()==Person.MALE)
recomendation=MovieGenre.PORN;
else
recomendation=MovieGenre.CHICKFLICK;
New Version, sure to win the million bucks:
if(user.getGender()==Person.MALE && user.getOrientation()==Person.STRAIGHT)
recomendation=MovieGenre.PORN;
else
recomendation=MovieGenre.CHICKFLICK;
Parent
I had a thought like this a while back... (Score:5, Interesting)
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go see porn sites (Score:3, Interesting)
Especially the newer blogish type pages where theres a gallery and a small selection underneath.
Not that I would know of course.
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Suggestion (Score:5, Insightful)
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Just a nitpick... If I mark, say, season 1 of series X as Not Interested, maybe it means I already own it and have no need to rent it, but still might want to see season 2. Of course, if I marked it as 1-star (Which I assume means "Utter crap"), then as you said, it should shut the hell up about the rest of the series.
I disagree. If you have it, you presumably have watched it and should give it a rating. You do have interest in it, or you would not have bought it. So things you mark as 1 star should prob
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I didn't like Star Wars:Episode I very much. Episode 4 was great though.
Right, so you might mark episode I, (technically number 4 by release order and prequels generally suck so I think this should be the ordering mechanism) as 2 stars or even 1. You wouldn't mark it as not interested, since from your comment you were interested enough to watch it. If, however, you were so disinterested in episode I so as to mark it as not interested (meaning you did not watch it and don't ever want to) then the chances
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I was about to mention that I mark things as Not Interested when I own them, to avoid being reccommended the rest (Usually because I prefer to buy series I like, and rent actual movies), but then I realized that fits into what you said perfectly.
Point conceded.
Re:Suggestion (Score:5, Funny)
For the record, this is a turning point in slashdot history. I'll forever remember where I was when I first saw those words in a slashdot comment. (Which of course is at work, sitting through a boring meeting.)
Parent
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Privacy issues? (Score:3, Interesting)
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To prevent certain inferences being drawn about the Netflix customer base, some of the rating data for some customers in the training and qualifying sets have been deliberately perturbed in one or more of the following ways: deleting ratings; inserting alternative ratings and dates; and modifying rating dates.
Plus all the usual replacing of IDs and such you'd expect. Looks like they're trying to avoid a repeat of the AOL debacle at least.
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RSSTimes (Score:5, Insightful)
Why is it that the Slashdot editors are just too damn lazy to look up the RSS feed links to these pages?
While this may be true, I wouldn't let it deter you. Collaborative filtering is a field that is far from dead. The interesting thing about collaborative filtering is that on the surface, it seems pretty straight forward but once you dig into the mechanics of it, there is actually a lot of playing you can do. Ironically, the way you display the data to the end user is often what determines how well of a job you did.
Allow me to take a naïve approach at this topic and say we generate a movie index of each person. I would have A Clockwork Orange and Koyaanisqatsi at 5 while The Ring 2 would be at the very low end. My friend might have similar movies. If he has A Clockwork Orange up there, you might be able to compute a Euclidean distance between us. However, this approach falls apart because no one has seen Koyaanisqatsi and of the 20 movies I've ranked highly, they are hard to find.
You don't have to stop there, however. You could also database the movies I marked as "uninterested" or the movies that were presented to me but I didn't vote on. Like if I had seen the offer to mark J-Lo's latest flop but didn't, wouldn't that tell you something about me?
So these caveats present themselves all along the way and, at the end computation, you have many different strategies for this data. For example, while you might not be able to link my friend an I through movies, how far apart are we on a nod network? What I mean is, if you plotted every user in their own dimension depending on the movies they ranked and attempted to compute as good a distance as possible between all users, how far would I be away from my friend by hopping on these nodes? There's a lot of information to be gleaned in this sort of friend-of-a-friend collaborative approach.
Now you need to present this information to the user. Do you just up and recommend him a movie? Do you take Amazon's approach and say "Other people did this -- so should you."? Or do you give them some sort of three dimensional flash plotting of you versus the people nearest to you? Do you allow the user to contact those closest to them? Those farthest away?
My point is that while 15 years of research has been done, it doesn't mean there's been 15 years of testing and implementation which, in the end of creating products, is where most of the importance lies.
About no-login links on /. (Score:3, Insightful)
I think it is the reason.
Slashdot can't send thousands of users with a fake referrer to NY Times. That link you provided is for people using RSS readers and subscribed to NY Times RSS feed.
I think they should talk with NY Times web team to allow slashdot readers with referrer=slashdot without needing login. They can arrange it for sure, this isn't a "no name" site.
It would be nice for NY Times for
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(FWIW, Powaqqatsi was a better flick, IMHO)
I know...credit reports! (Score:2)
Copy the Music Genome Project (Score:5, Interesting)
What they need to do is copy the methods of the Music Genome Project (www.pandora.com), and list a larger set of attributes for the films. This way it can recommend films by checking many more characteristics, such as director, tone, writer, or subject.
Re:Copy the Music Genome Project (Score:5, Informative)
What they need to do is copy the methods of the Music Genome Project (www.pandora.com), and list a larger set of attributes for the films. This way it can recommend films by checking many more characteristics, such as director, tone, writer, or subject.
In this contest, you run your own code and submit the results to NetFlix to be scored. This means that you can use any other data (e.g. A Movie Genome projct) you can compile to enhance your rankings. Netflix apparently specifically designed the contest to allow this.
Parent
Not just the movie characteristics. (Score:2)
But they also need ways to identify the characteristics of people's choices. Right now, one NetFlix account can be used by a whole family. So instead of getting 1 person's characteristic choices (teenage emo goth girl), you get those combined with the other family members (Dad's action films, Mom's chick flicks, Jr's teenage sex comedies).
Eventually, you'd end up with a movie genome cross indexed to a sub-culture.
only a million? (Score:3, Interesting)
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So, you could take the money from Netflix, use it to start your business, then license it to the other players, too.
Fix the problems with what they send me first (Score:5, Interesting)
On top of that, don't show me that it's available in my queue but send me something else instead. While I haven't asked netflix about this, I have asked blockbuster online, and I imagine they are both doing the same thing. The disc is "available" just not at the warehouse used to ship to me personally. Instead of basing one piece of information off of total stock and one off of local stock, base them both on the stock at the warehouse shipping to me.
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I thought Netflix users just ripped the movies to their hard drive for later viewing anyway?
Remove Artificial Supply Limitations (Score:3, Insightful)
Difficulties on the data-gathering end (Score:5, Interesting)
Not that marketers have a better handle, but simply that people will swear up and down that they would buy a peanut-butter-filled hot dog, that they loved the one they tried, and then don't actually buy any.
Don't believe me? Go see Snakes on a Plane. Nobody else did. (Sure, $33 million seems like a lot, but that's chump change for a major studio release these days.)
The best improvements will come from insights gained between the lines. You may have rated The English Patient eleventeen stars, but if your next seven rentals were all episodes of The Girls Next Door, which you only rated 3 stars, it certainly looks like you want more Hugh Hefner and less Ralph Fiennes.
The best data is the data that the subject doesn't realize he's giving you. Once you start imposing conscious choice on the ratings, you get only what they say they like, not what they really like.
Intractable problem - liking the movie, not genre (Score:4, Interesting)
I stopped rating movies after I found that I got recommended a lot of crap. Say I rent a slasher movie that, for its genre, is artfully done. I rate it high. Now I have recommendations for a bunch of worthless, straight-to-video stuff that I really don't want to see.
This is the real nut to crack, IMO. How do come up with an algorithm that rates 'quality,' an elusive concept that means different things to different people?
Not to mention, I'm fickle.
Re:Intractable problem - liking the movie, not gen (Score:2)
5 star rating is flawed (Score:4, Insightful)
The problem is is that that is my rating system. It works for me. But it does little good to anybody else because they are rating based purely on something else.
I think they need to implement the ability to rate more aspects of the movie. I'm sure some people out there rate the movie poorly if their disc is scratched or the transfer quality is poor even. A simple 1 to 5 system doesn't cut it. People rate things that aren't "Was the (romance) plot good?", "Do you like this director?", "Do you like these actors?". People rate things that aren't on the box.
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Just add racing stripes! (Score:2, Funny)
Define "better" (Score:2)
FROM tblMovies as m, tblAdvertisers as a
WHERE m.studio = a.studio
ORDER BY a.adRevenue DESC
I win.
Here's a problem to solve with much larger impact (Score:3, Interesting)
Re:Here's a problem to solve with much larger impa (Score:3, Informative)
This problem is already solved.
Wi
Common data (Score:3, Informative)
Of course, I'm biased since I had John Riedl as a professor in a few easy classes. I think he tried to spin off this research as a new company, but I'm not sure if it ever got off the ground.
One thing I'd really like to see has little to do with the quality of ratings, though. I'd like to be able to keep a common database of my ratings across multiple sites. At the moment, I've rated a number of movies at Netflix, MovieLens, and IMDb, but they aren't entirely consistent. Unfortunately, two of the sites use a ten-point system (IMDb has a ten-point scale, MovieLens goes up to 5 stars, but in half-star increments), while the other uses a five-point one (maybe six if you say "Not Interested"..).
Well, I'll have to poke around a bit with this stuff. I wouldn't be able to do much, though, since my level of knowledge in this arena is very limited...
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Anyone else have better luck?
Re:database? (Score:4, Informative)
Parent
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