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Help! My iPod
                                            thinks I’m emo.



                SXSW Interactive
            ...
Music recommendation is broken
   A recommendation that no human would make



           If you like Britney Spears ...

...
Help! My iPod thinks I’m emo
   What we are talking about today




                  Important?
                  Broken?...
Why do we care?
   Compulsory Long Tail slide




Monday, March 23, 2009
Why do we care?
   Compulsory Long Tail slide




Monday, March 23, 2009
Why do we care?
   Compulsory Long Tail slide




Monday, March 23, 2009
Why do we care?
   Compulsory Long Tail slide




Monday, March 23, 2009
State of music discovery
   We can’t seem to find the long tail



             Sales data for 2007
              - 4 milli...
State of music discovery
   We can’t seem to find the long tail



             Sales data for 2007
              - 4 milli...
State of music discovery
   We can’t seem to find the long tail



             Sales data for 2007
              - 4 milli...
State of music discovery
   We can’t seem to find the long tail



             Sales data for 2007
              - 4 milli...
Help! I’m stuck in the head
   The limited reach of music recommendation
               Popularity




                   ...
Help! I’m stuck in the head
   The limited reach of music recommendation




                                             ...
Help! I’m stuck in the head
   The limited reach of music recommendation




                                             ...
Help! I’m stuck in the head
   The limited reach of music recommendation




                                             ...
Help! My iPod thinks I’m emo




                         Why is music recommendation broken?




Monday, March 23, 2009
The Wisdom of Crowds
   How does collaborative filtering work?




                                   35%                  ...
The stupidity of solitude
   The Cold Start problem


             If you like Blondie, you might like the DeBretts ...


...
The stupidity of solitude
   The Cold Start problem


             If you like Blondie, you might like the DeBretts ...


...
The stupidity of solitude
   The Cold Start problem


             If you like Blondie, you might like the DeBretts ...


...
The Harry Potter Problem
   If you like X you might like Harry Potter




Monday, March 23, 2009
The Harry Potter Problem
   If you like X you might like Harry Potter




Monday, March 23, 2009
Popularity Bias
   Rich get richer - diversity is the biggest loser


                             Results of popularity b...
Popularity Bias
   Rich get richer - diversity is the biggest loser


                             Results of popularity b...
The Novelty Problem
   If you like The Beatles you might like ...




Monday, March 23, 2009
The Napoleon Dynamite Problem
   Some items are not easy to categorize




Monday, March 23, 2009
The Opacity Problem
   “If you like NiN you might like Johnny Cash” - why?




                                           ...
Hacking the recommender
   Recommenders can be easily manipulated for fun or profit




Monday, March 23, 2009
Hacking the recommender
   Recommenders can be easily manipulated for fun or profit




Monday, March 23, 2009
Help! My iPod thinks I’m emo




                         Fixing music recommendation




Monday, March 23, 2009
Fixing music recommendation
   Eliminating popularity bias and feedback loops




                                        ...
Fixing music recommendation
   Semantic-based recommendation




                                     pop legend dance div...
Fixing music recommendation
   Where does this information come from?
                                                    ...
Fixing music recommendation
   Content-based recommendation




                                              4
          ...
Content-based recommendation
   Using machines to listen to music

     Perceptual features audio:                        ...
Hybrid Recommendation
               The best of all worlds

            listener data                                    ...
What if?

           What if technology isn’t the answer?




                                No magic recommender?
      ...
Taste is irrational



             What makes people like things?*
             Social connections:
                 Who ...
Not all listeners equal
   Different types of listeners need different kinds of recommenders




Monday, March 23, 2009
Not all listeners equal
   Different types of listeners need different kinds of recommenders




                         ...
Not all listeners equal
   Different types of listeners need different kinds of recommenders




                         ...
Not all listeners equal
   Different types of listeners need different kinds of recommenders




                         ...
Not all listeners equal
   Different types of listeners need different kinds of recommenders



                          ...
Accept irrationality


             To make real discoveries possible:

             Offer unique presentation

          ...
Unique Presentation & Editorial
   Ishkurs’ guide to Electronic Music (http://techno.org)




Monday, March 23, 2009
Context & Interaction
   Guitar hero / Rock Band gameplay




Monday, March 23, 2009
Context
   What’s on her playlist? imeem (http://imeem.com), social playlists




Monday, March 23, 2009
Context & Meaning via Editorial
   14 Tracks: Weekly themed selections (http://14tracks.com)


    14 Tracks that make you...
Playful Presentation & Meaning
   thesixtyone (http://thesixtyone.com)




Monday, March 23, 2009
Visible Context & Meaning
   The Hype Machine




Monday, March 23, 2009
Meaning via Authoritative Editorial
   Pitchfork’s Best New Music pages (http://pitchforkmedia.com)




Monday, March 23, ...
The Future of Music Discovery
   Listen, Learn, Understand, Engage - for all music.




Monday, March 23, 2009
The Future of Music Discovery
   Listen, Learn, Understand, Engage - for all music.




Monday, March 23, 2009
The Future of Music Discovery
   Listen, Learn, Understand, Engage - for all music.




Monday, March 23, 2009
The Future of Music Discovery
   Listen, Learn, Understand, Engage - for all music.




Monday, March 23, 2009
The Future of Music Discovery
   The challenge




                         Music               Music
                    ...
The Future of Music Discovery
   Editors, people, serendipity. Scaled.




                 image by luc legay (CC)

Monda...
Help! My iPod
                                thinks I’m emo.
         Questions?



       Paul Lamere
           the.ech...
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Hybrid Recommendation The best of Help! My iPod thinks I'm emo.

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Hybrid Recommendation
The best of all worlds

listener data Hybrid Recommender

preference editorial
user history
35% 4% 62% 8% 60%

recommendations
12% 18% 17% 34% 21%


audio data 4% 49% 5% 48% 7%


artist
collaborative filterer

audio
analysis

track
web data
content-based

user
adj Term K-L bits np Term K-L bits
random guessing is:
aggressive 0.0034 reverb 0.0064
softer 0.0030 the noise 0.0051
synthetic 0.0029 new wave 0.0039
a Na
KL = log punk 0.0024 elvis costello 0.0036
(a + b) (a + c)
N sleepy 0.0022 the mud 0.0032

cultural
funky 0.0020 his guitar 0.0029
b Nb
+ log noisy 0.0020 guitar bass and drums 0.0027
(a + b) (b + d)
N angular 0.0016 instrumentals 0.0021

analysis
c Nc acoustic 0.0015 melancholy 0.0020
+ log romantic 0.0014 three chords 0.0019
(a + c) (c + d)
N
d Nd Table 2. Selected top-performing models of adjective and
+ log
(b + d) (c + d)
semantic-based
N noun phrase terms used to predict new reviews of music
with their corresponding bits of information from the K-L
(3)
distance measure.
This measures the distance of the classifier away from a
degenerate distribution; we note that it is also the mu-
7.4. Review Regularization
tual information (in bits, if the logs are taken in base 2)
Monday, March 23, 2009

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