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눈으로 듣는 음악 추천 시스템-2018 if-kakao

음악 추천의 Song Vector(Latent Factor)를 탐색하는 자료입니다
IF-Kakao 2018에서 발표한 자료 입니다.

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눈으로 듣는 음악 추천 시스템-2018 if-kakao

  1. 1. ~
  2. 2. ~
  3. 3. ~
  4. 4. ~ Matrix Factorization Word2Vec Deep Learning on audio
  5. 5. ~
  6. 6. .. Dance the night 1 Power up Forever young Viva la viva  Thinking out Loud  Counting Stars Something Just Like This
  7. 7. .. Dance the night 1 Power up Forever young Viva la viva  Thinking out Loud  Counting Stars Something Just Like This
  8. 8. .. Dance the night 1 Power up Forever young Viva la viva  Thinking out Loud  Counting Stars Something Just Like This
  9. 9. Push 1.5 5.6 User 18 DJ 3 / Song Vector .
  10. 10. 1.5 5.6 User 18 DJ 3 / Song Vector .
  11. 11. 1.5 5.6 User 18 DJ 3 / Song Vector . Feedback CF(Collaboration Filter) Contents CBF(Contents Based Filtering)
  12. 12. ?
  13. 13. ? …
  14. 14. ? filtering . … / 7080 X- 2000’ 2010’ 2018’ Top100 Rare - …..
  15. 15. 40D Dense Vector - Matrix Completion via ALS - User/Item Latent Feature Feedback Log(8day) - 4.3M(User) X 2.1M(Song) - 388M None zero values (Song)
  16. 16. 40D Dense Vector - Matrix Completion via ALS - User/Item Latent Feature Feedback Log(8day) - 4.3M(User) X 2.1M(Song) - 388M None zero values (Song) (Song) Vector Vector .
  17. 17. ? , .
  18. 18. Low level Feature Genre Classification Network
  19. 19. Low level Feature Genre Classification Network(Song) Vector Vector .
  20. 20. - 2004 12 1553
  21. 21. - 2004 12 1553 Stream + W2V
  22. 22. - 2004 12 1553 2004 12 Stream + W2V
  23. 23. - 2004 12 1553 Stream + MF 1553
  24. 24. Sampling 5M -> 16K Song Meta Mapping , , Stream Song Segmentation Light, Medium, Heavy, Extreme Dimension Reduction 40D -> 2D
  25. 25. Sampling 5M -> 16K Song Meta Mapping , , Stream Song Segmentation Light, Medium, Heavy, Extreme Dimension Reduction 40D -> 2D 5M Songs Top 1,000 Songs 15,000 Songs Uniform Sampling 1,000 Songs + = 16,000 Songs
  26. 26. Sampling 5M -> 16K Song Meta Mapping , , Stream Song Segmentation Light, Medium, Heavy, Extreme Dimension Reduction 40D -> 2D t-SNE
  27. 27. Sampling 5M -> 16K Song Meta Mapping , , Popularity Song Segmentation Light, Medium, Heavy, Extreme Dimension Reduction 40D -> 2D
  28. 28. Sampling 5M -> 16K Song Meta Mapping , , Popularity Song Segmentation Light, Medium, Heavy, Extreme Dimension Reduction 40D -> 2D
  29. 29. • Heavy • Top1000 Top1000 . • Popularity . • .
  30. 30. OST R&B CCM J-POP POP Global
  31. 31. Popularity
  32. 32. Light, Medium Song
  33. 33. Top1000 Top1000
  34. 34. • • MF • Top1000 Top1000 .
  35. 35. • • • Top1000 Top1000 .
  36. 36. 1,037 .
  37. 37. 45.2% 60.1% 59.9%
  38. 38. Stream Stream Stream
  39. 39. Stream Stream Stream 1. Streaming 1 2. Streaming 1 Streaming 97
  40. 40. Stream 1. 100 ~ 10,000 . 2. .
  41. 41. Song Vector Popular .
  42. 42. / / CCM /
  43. 43. .

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  • kchman

    Aug. 18, 2019
  • jayuloy

    Aug. 19, 2019
  • ssuser1f784c

    Aug. 19, 2019

음악 추천의 Song Vector(Latent Factor)를 탐색하는 자료입니다 IF-Kakao 2018에서 발표한 자료 입니다.

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