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Music Social Networks Apple

Going Head To Head With Genius On Playlists 174

Posted by timothy
from the put-that-man-down dept.
brownerthanu writes "Engineers at the University of California, San Diego are developing a system to include an ignored sector of music, dubbed the 'long tail,' in music recommendations. It's well known that radio suffers from a popularity bias, where the most popular songs receive an inordinate amount of exposure. In Apple's music recommender system, iTunes' Genius, this bias is magnified. An underground artist will never be recommended in a playlist due to insufficient data. It's an artifact of the popular collaborative filtering recommender algorithm, which Genius is based on. In order to establish a more holistic model of the music world, Luke Barrington and researchers at the Computer Audition Laboratory have created a machine learning system which classifies songs in an automated, Pandora-like, fashion. Instead of using humans to explicitly categorize individual songs, they capture the wisdom of the crowds via a Facebook game, Herd It, and use the data to train statistical models. The machine can then 'listen to,' describe and recommend any song, popular or not. As more people play the game, the machines get smarter. Their experiments show that automatic recommendations work at least as well as Genius for recommending undiscovered music."
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Going Head To Head With Genius On Playlists

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  • So, not at all? (Score:5, Informative)

    by BadAnalogyGuy (945258) <BadAnalogyGuy@gmail.com> on Thursday November 05, 2009 @06:33PM (#30000854)

    It's well known that radio suffers from a popularity bias, where the most popular songs receive an inordinate amount of exposure. In Apple's music recommender system, iTunes' Genius, this bias is magnified. An underground artist will never be recommended in a playlist due to insufficient data. ...
    Their experiments show that automatic recommendations work at least as well as Genius for recommending undiscovered music

    So, not really so much at all...?

  • This is so true. (Score:1, Informative)

    by Anonymous Coward on Thursday November 05, 2009 @06:44PM (#30000988)

    I really enjoy classical guitar music. Apple's genius selection for the type of music I enjoy is so bad I just turned it off.

  • by SlashdotOgre (739181) on Thursday November 05, 2009 @06:52PM (#30001110) Journal

    Actually I've found last.fm's recommendation system works extremely well; so well in fact that I constantly have a tab open to it when I'm browsing music stores like eMusic (eventually I want to write a little app for this purpose using last.fm's API, but I digress). For those unaware, last.fm users submit what they're listening to through automated plugins (and the supported apps list is huge and very platform independent, I personally use both Amarok 1.4 and MPD); one of the things last.fm does with this music is identifies your "neighbors" (people with similar lastes, i.e. 8 of our top 10 artists are identical). I've found that one of the best ways to find new music is by browsing what my neighbors are listening to and checking out any of their top bands that I'm not familiar with. They also list related artists by correlating this information (e.g. the majority of users who have Band A as a favorite artist also like Band B). Another useful feature is being able to check what an artists most played songs are (great for when it's an artist you never heard of). With that said, I'm definitely interested in seeing what recommendations come from this UCSD team (and not just because I'm an alumnae) as I'm always interested in finding new artists, especially smaller and local ones.

  • Re:Wow. (Score:3, Informative)

    by 0100010001010011 (652467) on Thursday November 05, 2009 @06:54PM (#30001138)

    I've had great success with Gnoosic [gnoosic.com]

  • by ptaff (165113) on Thursday November 05, 2009 @07:05PM (#30001262) Homepage

    For possibly the great majority of the population, music can be compared to fashion; does not really matter if the art is good per se, what matters is the trend and popularity, on a local scale (what my friends listen to) and global scale (media).

    With the rock'n'roll revolution in the fifties, lots of teenagers liked that new music in part because it wasn't their parents' music. Same story can be said of disco, rap and grunge.

    Problem with the long-tail approach is that people mostly judge music by non-musical criteria.

  • by Rib Feast (458942) on Thursday November 05, 2009 @08:23PM (#30001872)

    The biggest problem is that Apple is probably the closest internet-based distribution system to the record labels of old. Perhaps this is an "appeal to the masses" approach or to get onside with the labels.

    The downside of this is that a collaborative filter based on genre and sales will never go deep. I doubt they'd ever use pearson's correlation coefficient seriously enough to offset the "this is the new hit everyone listens to so you should too".

    I guess it comes down to musical integrity to the extent of ignoring trends to deliver truly accurate results... or hit 90% of the market with a simple solution that probably makes them more money and makes the record labels easier to deal with.

    Glad to see they're thinking different and aren't just playing to the status quo.

  • by lucubrationowl (1671460) on Thursday November 05, 2009 @08:53PM (#30002036)

    Stop being arithmetic supergeeks wanting to put everything inside a box, and start figuring out how to get all these weird unpredictable people to input valuable data into your system.

    Google figured this out more than a decade ago, so why are we still seeing stupid mathematical and "pattern-based" algorithms every year?

    The neural network is trained on crowd-sourced data. TRANSLATION: These supergeeks actually DID figure out how to get all these weird unpredictable people to input valuable data into their system. The solution they designed is that people will play their Facebook game, herdit.org, and the statistically significant answers to the quiz game are tagged to the song clips. These tagged song clips are then used as a training data set for the neural network. The machine algorithm is a result of the collective intelligence of all the players of herdit.org

  • Re:Wow. (Score:2, Informative)

    by rockNme2349 (1414329) on Thursday November 05, 2009 @09:10PM (#30002134)

    I remember reading somewhere in the pandora algorithm that you should only click "Thumbs Up" for songs you really like, not every song you like. If you like a song, but there are aspects of it you don't like then don't select anything, just let it play.

    I know this isn't as nice as being able to select individual features of a song, but what are you going to do?

  • by weston (16146) <{westonsd} {at} {canncentral.org}> on Friday November 06, 2009 @06:22AM (#30004160) Homepage

    The Academic fantasizes about the Technocrat that will eventually lead us all into utopia by prescribing us "plebes" the perfect formula to live our lives

    For example, the Chicago or Austrian Schools of Economics.

  • by mcgrew (92797) * on Friday November 06, 2009 @10:37AM (#30005478) Homepage Journal

    Well, when possible the internet is the best place; you can get "radio" from just about every radio station in the world. Go to KSHE [kshe95.com] for the oldest FM stereo rock station in the world, [kuro5hin.org] who played "classic rock" before it was classic and still do, along with some of today's dreck. On Sunday night they play seven albums in their entirety, back to back.

    College stations are great, too. The one here in Springfiled, WQNA, [slashdot.org] is the only station I've ever heard where you can hear Tennessee Ernie Ford followed by the Dead Kennedies, followed by Johnny Cash (The DKs are a 70s punk band). Sunday mornings is old 30s and 40s jazz, noon is a blues show, Tuesday nights there's a "hardcore" show followed by a country oldies show. Wednesday nights they have belly dancing music, etc.

The number of arguments is unimportant unless some of them are correct. -- Ralph Hartley

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