SlideShare a Scribd company logo
3 flow considerations
 about implementing
   similar playlists
WOULD NOT WORK:

compile the top X
  (eg. 10) list of
 artists of each
     playlist
                              sort this top X list
                                 by artist_ID
  compare two of
 these sorted lists
   with Pearson
  Correlation (=r)
    r can range from -1 to 1,
    where 0 is no linear correlation
    and 1 & -1 are perfectly linear



 if(abs(r)) = close to 1, high linear correlation

Wouldnt work because, if artist ID's differ just one, still there
would be high linear correlation, but music completely different
WOULD WORK:

compile the top X
  (eg. 10) list of
  artists of each
      playlist
                    compare the X
                 members of List A
                  to the X members
                       of List B
 foreach exact hit,
  add a +1 to the
        score

   score can range from 0 to X,
   where 0 is no similarity and X
   is perfectly similar


if(score = close to X) we have a very similar list

        a lists based upon absolute matching artists.
WOULD WORK ADVANCED:
compile the top X
  (eg. 10) list of
  artists of each
      playlist       retrieve single
                   Tag for each artist
                         (genre)
                compare the X
               Tags of List A to
              the X Tags of List
                      B
foreach exact hit,
 add a +1 to the
       score

   score can range from 0 to X,
   where 0 is no similarity and X
   is perfectly similar


  if(score = close to X) we have a very similar list

       in this case, lists based upon similar music styles,
               instead of absolute matching artists.

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Contemplated these 3 Flows for Playlist Similarity

  • 1. 3 flow considerations about implementing similar playlists
  • 2. WOULD NOT WORK: compile the top X (eg. 10) list of artists of each playlist sort this top X list by artist_ID compare two of these sorted lists with Pearson Correlation (=r) r can range from -1 to 1, where 0 is no linear correlation and 1 & -1 are perfectly linear if(abs(r)) = close to 1, high linear correlation Wouldnt work because, if artist ID's differ just one, still there would be high linear correlation, but music completely different
  • 3. WOULD WORK: compile the top X (eg. 10) list of artists of each playlist compare the X members of List A to the X members of List B foreach exact hit, add a +1 to the score score can range from 0 to X, where 0 is no similarity and X is perfectly similar if(score = close to X) we have a very similar list a lists based upon absolute matching artists.
  • 4. WOULD WORK ADVANCED: compile the top X (eg. 10) list of artists of each playlist retrieve single Tag for each artist (genre) compare the X Tags of List A to the X Tags of List B foreach exact hit, add a +1 to the score score can range from 0 to X, where 0 is no similarity and X is perfectly similar if(score = close to X) we have a very similar list in this case, lists based upon similar music styles, instead of absolute matching artists.