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Build a Better Netflix, Win a Million Dollars? 197

Posted by CmdrTaco
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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Build a Better Netflix, Win a Million Dollars?

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  • by garcia (6573) on Monday October 02, 2006 @11:00AM (#16276999)
    If no one wins within a year, Netflix will award $50,000 to whoever makes the most progress above a 1 percent improvement, and will award the same amount each year until someone wins the grand prize.

    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 ;)
    • Re: (Score:3, Informative)

      by curunir (98273) *
      From the rules, it looks like your submission isn't code, it's a processed dataset. It's only in the terms for winning are that you have to explain your method to them (so that they don't get bitten by a horribly obfuscated entry) and have to non-exclusively license your submission to Netflix (it looks like you retain copyright and can license it to others if you so choose).

      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
    • Re: (Score:3, Informative)

      by stonecypher (118140)
      If you read NetFlix' prize site [netflixprize.com], you'll find that they give clear cut statistical requirements for winning that are well defined. It's actually quite impressive the detail into which they go; it's clear that they want real engineers on this, and that they're willing to get seriously specific in order to make sure people know what's what.
  • I officially announce I will be entering BigAtticHouse's Vectorspace Database into the melee. At least to see what might come of it.
  • by jimstapleton (999106) on Monday October 02, 2006 @11:02AM (#16277015) Journal
    Says one researcher: "You're competing with 15 years of really smart people banging away at the problem."


    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.
    • I am neither teenage or a hacker...but I still find the "challenge" somewhat unchallenging.

      Simply filter their existing result set to exclude titles that are in a genre that the user has NEVER rented anything from and that would be a huge improvement!

  • Simple (Score:5, Funny)

    by Anonymous Coward on Monday October 02, 2006 @11:02AM (#16277023)
    if(user.getGender()==Person.MALE)
    recomendation=MovieGenre.PORN;
    else
    recomendation=MovieGenre.CHICKFLICK;

    And of course, slashdot must have sensed my post as my image word is "pervert"
  • ..except, instead of making it open to the community (which is not a bad idea, I must say) I thought of having Google do it. This is, perhaps, IMHO, a much better idea. Now, what we really need is a Movie Genome Project, much like the Music Genome project that lead to Pandora.
    • by Boone^ (151057)
      Pandora's recommendations are really spot on. I rarely have to give one the thumbs down.
  • go see porn sites (Score:3, Interesting)

    by LiquidCoooled (634315) on Monday October 02, 2006 @11:03AM (#16277035) Homepage Journal
    They have decent tech for building similar/recommended alternative pages.
    Especially the newer blogish type pages where theres a gallery and a small selection underneath.

    Not that I would know of course.
    • by MustardMan (52102)
      What kind of horrible person are you, to make a statement like this and not link to an example of the tech in action... you know, for illustrative purposes.
  • Suggestion (Score:5, Insightful)

    by 99BottlesOfBeerInMyF (813746) on Monday October 02, 2006 @11:03AM (#16277045)
    As a NetFlix user I have one suggestion for their recommendation system that can make it much better. Make it aware of the connection between series. That is to say, If you rent season 1 of something, suggest season 2, not season 4 (even if season 4 has better review ratings). If I mark season 1 of something as "not interested" instead of giving it a user rating, don't suggest every other season of that same show at the top of my recommendations. I mean how many times do I have to tell you I don't want to see any season of "Friends" ever, even if you pay me?
    • by tourvil (103765)
      I wish Netflix would group an entire TV series as a recommendation instead of each individual season. I rented a couple DVDs of Dr. Who and marked them as 5 stars. Now my recommendation page is flooded with Dr. Who. I've already seen some of the series, so I already know I'll probably like the other seasons. I don't need Netflix to tell me that because it's obvious. I'd rather the recommendation system suggest DVDs that I might not have ever heard of or haven't thought about.
      • I can see where you're coming from...but what if you weren't aware that season X of series Y has already been released on DVD? It'd be kinda nice to be notified when the latest one became available.
    • And consider various versions of movies to be the same movie. If I'm not interested in E.T., I'm not going to be interested in any of the quinannual release, the special edition, the extra special edition, the extreme edition, or the super secret special extreme mega edition which actually has guns.
  • Privacy issues? (Score:3, Interesting)

    by Vultan (468899) on Monday October 02, 2006 @11:05AM (#16277063)
    How will they handle privacy issues? Don't the same issues appear here that appeared with the AOL data this summer? With enough ratings you can narrow down to a specific person, and then find out about all the pr0n that this person has been getting as well.
    • The AOL search ratings were different because the searches could include things like cities, proper names, phone numbers, and other such pieces of identifiable information. The movie ratings have none of that. You might be able to dig through the list and find the person who rated "Goat donkey pr0n" highly and laugh at them, but there's no information there that'll tell you who it was.
    • Re: (Score:3, Informative)

      by Cruise_WD (410599)
      From http://www.netflixprize.com/ [netflixprize.com] :

      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.
    • Re: (Score:3, Insightful)

      by Shihar (153932)
      The AOL search was an issue because you could look at search requests for places and figure out where someone was very quickly. If I use Google to plot the rout to the nearest IKEA or porn store, it is a pretty simple matter to trace back who someone is. Short of some serious stupidity, I couldn't imagine Netflix giving away any valuable information in identity theft. A list of movies is highly unlikely to lead to anyone's address or identity.
  • RSSTimes (Score:5, Insightful)

    by eldavojohn (898314) * <`eldavojohn' `at' `gmail.com'> on Monday October 02, 2006 @11:05AM (#16277065) Journal
    In a quest to better movie recommendations, Netflix is opening their database (nytimes, registration and first child required)...
    Not quite, you can find it here [nytimes.com] (or the minimalist version [nytimes.com] for anyone sick of ads).

    Why is it that the Slashdot editors are just too damn lazy to look up the RSS feed links to these pages?

    The problem is not easy. Says one researcher: "You're competing with 15 years of really smart people banging away at the problem."
    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.
    • by Ilgaz (86384)
      You can trick the NY Times personally but you can't do it from a front page of a widely popular commercial site.

      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
    • by Scutter (18425)
      However, this approach falls apart because no one has seen Koyaanisqatsi

      Well...almost no one. ;)
      • Re: (Score:3, Informative)

        by cei (107343)
        Correction: No one has stayed awake through Koyannisqatsi.

        (FWIW, Powaqqatsi was a better flick, IMHO)
        • by Scutter (18425)
          Correction: No one has stayed awake through Koyannisqatsi.

          (FWIW, Powaqqatsi was a better flick, IMHO)


          See, I liked the first one better, and I didn't have any trouble staying awake. I like Philip Glass and I like Francis Ford Coppola, though.
    • The problem with recommendations is that it can only determine what to recommend based on what you've rented, what you've marked you like and what other people who rented the same stuff liked also.

      They are leaving out a whole aspect of psychology. The problem is that they have a 2 day lead time to get the content to you. So, it's not just a matter of them asking what your mood is and then providing you with the movie. Instead, they have to predict how you will be feeling 2 days from now and send you the
  • Link everyone's credit report into their movie preferences; I'll bet your complete credit history would give them a 5-10% better chance of picking your movies. But seriously...why isn't this just a regression exercise?
  • by Zaphod-AVA (471116) on Monday October 02, 2006 @11:14AM (#16277179)
    The problem with recommendation systems is that they use too little information to catagorize their subject.

    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.
    • by vontrotsky (667853) on Monday October 02, 2006 @11:33AM (#16277447)
      The problem with recommendation systems is that they use too little information to catagorize their subject.

      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.
    • Yes, they need more characteristics of movies.

      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.
      • Netflix already lets you set up queues for each person in the house. However, what they need to do to make this more useful is to have a round robin system for shipping movies. Right now they make you assign a set number of discs to each queue. If you are on the 1 movie at a time plan, you can only setup 1 queu at a time to be receiving discs. When my wife and I had netflix, I'd have to log in each time I sent back a disc and reassign the 1 available disc to the other queue. I could see this being annoying
    • Encourage end-user tagging, compare on popular tags for matching a la LJ "people who have the most in common" search.

      Or leech off of IMDB's recommendation system, which seems to be quite good.
  • only a million? (Score:3, Interesting)

    by StandardDeviant (122674) on Monday October 02, 2006 @11:17AM (#16277219) Homepage Journal
    If you can beat "15 years of really smart people", then your work product probably has more than a million dollars in value if you were to license it out to places like Amazon, eBay, Netflix, etc. Even a 1% improvement in revenues from a 1% improvement in recommendation accuracy is probably worth more than 50K, if sold to the major e-tailers. On the other hand, if you just want an interesting problem to screw around with in your spare time and don't want to go through the bother of forming a company in order to monetize that work, this is a pretty cool opportunity.
    • Re: (Score:2, Insightful)

      To win and take home either prize, your qualifying submissions must have the largest accuracy improvement verified by the Contest judges, you must share your method with (and non-exclusively license it to) Netflix, and you must describe to the world how you did it and why it works.

      So, you could take the money from Netflix, use it to start your business, then license it to the other players, too.
    • All jobs work this way (or at least they should). Return on Investment. In order for a company to make money, they will pay you a wage. Hopefully you will produce work that is at minimum equivalent to the amount that they pay you. If not, then they will be losing money employing you and if they have decent reporting/management will probably fire you.

      Many companies do offer incentive programs (more likely for upper level positions), but is still just a percentage of the actual "value" that you created,
      • by Khashishi (775369)
        The whole problem with this argument is that it is the worst execs are overpaid as much as the best. http://www.dolmatconnell.com/resources/2006DCPTech 100Study.pdf [dolmatconnell.com]
        • Warren Buffet, one of the most successful investors in the US, CEO of mega-firm Berkshire Hathaway, makes good arguments in several of the Berkshire Hathaway annual reports that CEOs are dramatically overpaid.
  • by Jimmy King (828214) on Monday October 02, 2006 @11:17AM (#16277227) Homepage Journal
    I wish they'd fix the problems in the logic determining what they actually send me from my queue before fixing problems with what they recommend to me. If I've got season 1 of a show in my queue prior to season 2, don't start sending me season 2 because some disc of season 1 is unavailable (which has happened to me multiple with both netflix and blockbuster online), send me something else completely. They've got the tech to keep one season of a tv show in order, it can't possibly be that difficult to extend that to keeping multiple seasons of a show in order.

    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.
    • Re: (Score:3, Funny)

      by nine-times (778537)
      They've got the tech to keep one season of a tv show in order, it can't possibly be that difficult to extend that to keeping multiple seasons of a show in order.

      I thought Netflix users just ripped the movies to their hard drive for later viewing anyway?

  • by dduardo (592868) on Monday October 02, 2006 @11:23AM (#16277301)
    If Netflix doesn't have the movie in stock it should burn the movie on demand.
    • Unfortunately, under current US law, that's not up to NetFlix, but rather the company which holds the license on the movie. Currently, they do not allow any such behavior. The first content producer to allow something like that will make a small fortune.
  • by jfengel (409917) on Monday October 02, 2006 @11:24AM (#16277319) Homepage Journal
    Any marketer will tell you that what people tell you they want and what people actually want are very different things. Even if people answer honestly, the data you gather is often unreliable: people simply don't have as good a handle on what they want as they think they do.

    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.
    • by hoggoth (414195)
      > what people tell you they want and what people actually want are very different things

      It's the difference between scientists and engineers trying to decide what activities seem more dangerous, and actuarians using real historical data to rate activities. Guess which method insurance companies use when their money is on the line...

    • this is a little bit off-topic, but...

      an excellent book which covers, amongst many other things, how people do behave over how they say they'll behave is Freakonomics [amazon.co.uk].

      for example, they cover how people behave about race and dating, whilst people SAY they have little preference, analysis from dating agencies shows the opposite. Even some game show stats are used to prove people are prejudiced.

    • by metamatic (202216)
      Don't believe me? Go see Snakes on a Plane. Nobody else did.

      Did anyone say they wanted to see it, though? I saw a lot of people mocking it, but I didn't see any non-ironic expressions of enthusiasm.

  • by OakDragon (885217) on Monday October 02, 2006 @11:29AM (#16277383) Journal

    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.

    • How do come up with an algorithm that rates 'quality,'
      Phaedrus did this ages ago.
    • by kthejoker (931838)
      Well, if you think about it objectively, you find that genre is a terrible way to recommend movies. Consider:

      Movie A is an artful horror film (we'll even give it a bonus point for originality.) Movie B is a low budget straight to video rehash of Movie A.

      What are the differences between the two?

      A) Budget / production values.
      B) Production company.
      C) Actors.
      D) Crew, particularly director / writer / producer.
      E) Originality of script. (This is kind of subjective, but surely a remake of a movie is less original t
      • "But saying all romantic comedies are alike because they are romantic comedies is wrongheaded."

        It all depends on how dedicated to the genre you are. If you liked everything from Event Horizon, to Evil Dead, to Bram Stoker's Dracula, then there probably aren't too many horror movies wouldn't at least mildly enjoy.

        But if you only ever rent Action movies if they star Tom Cruise, then your high War of the Worlds rating wouldn't necessarily imply you'd also enjoy Armageddon.
  • by BMonger (68213) on Monday October 02, 2006 @11:31AM (#16277413)
    I personally weigh movies on a number of different factors. I might give 3 stars to a movie because it has 4 of my favorite actors in it even if I didn't care for the plot. I might give 3 stars to a different movie with horrible acting but interesting camera angles (From Dusk Til Dawn 2). I tend to average out my ratings dependent on many things a movie has to offer.

    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.
    • by AceCaseOR (594637)
      Personally, I wouldn't mind if NetFlix added a 1/2-star rating to their user ratings. They do half-star ratings for their reccomendations, after all.
    • by kthejoker (931838)
      The predominant problem with any movie ratings system is not the number of stars or the granularity of the rating.

      The major problem is, simply put, movies are not treated as a disposable commodity.

      I worked at a radio station for several years, and one of my jobs was to review CDs for library status. Listening to an entire CD takes anywhere from 30 to 60 minutes - simply impossible. So, you resort to fast-forwarding, previewing, and generally getting a feel for an album. Quickly you separate the wheat from t
  • And some macaroni pieces.
  • SELECT TOP 10 title
    FROM tblMovies as m, tblAdvertisers as a
    WHERE m.studio = a.studio
    ORDER BY a.adRevenue DESC

    I win.

  • BitTorrent!!! :)
  • by Yogs (592322) on Monday October 02, 2006 @12:08PM (#16278065)
    Disclaimer: I subscribe to the same sort of service, except through blockbuster... maybe Netflix does have this feature. My wife and I share a queue... I imagine many, many of these queues are shared. We have very, very different tastes in movies. Instead of getting recommendations that suit us both (which is next to impossible), the recommendations just get very, very confused. If I could just keep my and her recommendations from tangling, we would both have an easier time.
    • Disclaimer: I subscribe to the same sort of service, except through blockbuster... maybe Netflix does have this feature. My wife and I share a queue... I imagine many, many of these queues are shared. We have very, very different tastes in movies. Instead of getting recommendations that suit us both (which is next to impossible), the recommendations just get very, very confused. If I could just keep my and her recommendations from tangling, we would both have an easier time.

      This problem is already solved.

      Wi
  • Common data (Score:3, Informative)

    by Mike Hicks (244) * <hick0088@tc.umn.edu> on Monday October 02, 2006 @12:18PM (#16278217) Homepage Journal
    I see that the NYT article linked to just about everything except MovieLens [umn.edu]. I've used the site, and folks might like to try it out. It looks simple, but it's fairly nice, having some of those fun dynamic pages that are all the rage these days. One neat thing in comparison to Netflix is that it will give a projected star rating for you, rather than simply saying "Recommended".

    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...
  • # Netflix has more than 65,000 titles and more than 42 million DVDs total.

    # Netflix has more than 1 billion movie ratings from customers. The average subscriber has rated more than 200 movies.

    # Netflix members select approximately 60 percent of their movies based on movie recommendations tailored to their individual tastes.

    # Netflix's members rent more than 95 percent of all titles in the Netflix library each quarter.

    http://web.netflix.com/MediaCenter?id=1005&hnjr=8 [netflix.com]

  • Here's hoping somebody can fix the current system, because NetFlix and I are at a stalemate. With 1,324 movies rated, NetFlix gives me 0 recommendations because it has become quite confused about my taste in films.

    Once, I rented and liked a Devo DVD, so it recommended every band with a concert movie, but I don't like every band and started marking things "Not interested". Then, I added a Sarah Silverman disc to my queue, which NetFlix took to mean that I love all stand-up comics, especially those on the B

  •   Did anyone realize that Netflix is releasing 100 million of anonymous customer data? I thought /. was all for privacy. This just prooves that when it's $1 million dollars at stake, /. users don't care about privacy.

    Netflix also needs to introduce a dvd iso download service. In an age where most people own dvd burners, Why the hell not open dvd iso download service?
  • If I both liked Shrek II and The Motorcycle Diaries and Maria Full of Grace, and you liked Shrek II, does this mean you'll like the other 2? Absolutely not necessarily. The problem with the recommendation system is the limitation in -expression- of rating. A 1 to 5 star scale for every movie? It will never work.

    Combine tagging with rating and you'll find a much better recommendation system.

    i.e.: "Shrek II: cartoon, comedy, satire, Mike Myers; 4.5 stars" vs. "Shrek II: 4.5 stars" and "The Motorcycle Diaries:
  • My problem is that I rate the movies I watch very high. Why? Because if they were crappy movies I wouldn't have rented them anyway! I usually know something about a movie before I rent it, even if it's just the viewer reviews on NetFlix. My ratings are 3, 4 or 5, only very rarely do I give out a 1 or 2.

    Consequently NetFlix thinks I like everything. While the system is smart enough to not recommend Martin Lawrence movies, it usually gives me movies I'm simply not interested in. Or at the other extreme, it gi
    • Eddie Izzard: Dress to Kill - WTF?

      Hilarious. Seriously, I thought "oh, HELL no" when it was chosen as "the movie we are going to watch tonight", but I laughed my ass off. Le singe est dans l'arbre.
  • This is an easy problem. Simply write a predictor algorithm to compare the affinity characteristics of a given film to the affintiy characterisitcs of a given subscriber. Based on the goodness of fit, probabilities of acceptance can be assinged and recommandations made. "You like Romances more than Comedies, and both of them more than Westerns? OK, based on the weights you've given, High Noon isn't for you, but Young Frankenstein might be better."

    One problem, how many dimensions ARE there to human affin
  • I hope Amazon... (Score:2, Interesting)

    by GigG (887839)
    I certainly hope Amazon chooses to license anything that comes out of this. I've been a Amazon customer for about 10 years and have bought a couple of hundred books from them. For the first 2 or 3 years they gave me pretty good recomendations and I found a number of new authors that I probably wouldn't have started reading. Over the last few years they never catch a new author and suggest them.
  • Deja vu Netflix!

    The First one is the age olde "frame problem". This is IT taking a perfectly good database and expecting it to be an even better recommendation system.

    Airlines hit the same wall decades ago. They had databases of flights, seats and routes - all excellent. But they really wanted a reservation system based upon ticketing against that database. They finally recognized that nothing less than a mainframe was needed.

    The answers you get is all in how you frame the question. Starting with "dat

Dynamically binding, you realize the magic. Statically binding, you see only the hierarchy.

Working...