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Recommendation @Deezer

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Talk given by Benoit Mathieu during the RecsysFR meetup on March 22nd, 2016.

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Recommendation @Deezer

  1. 1. RecSysFr #3 Recommendation @Deezer RecSysFr, Paris, 2016 June 22th B. Mathieu, Head of Data Science
  2. 2. Deezer /01 RecSysFr #3
  3. 3. Deezer overview RecSysFr #3 ● 420 employees in 20 cities ● 5M albums ● 40M tracks ● 100M playlists ● 16M MAU ● 6M subscribers
  4. 4. ● ~500 servers ● 4.5 PB storage for audio files ● 1.5 TB of logs / day ● ~1B requests / day ● ~30k new albums each week ● Hadoop cluster with 1.5PB storage, 4TB RAM, 1000+ vcores Some technical numbers RecSysFr #3
  5. 5. Recommendation opportunities /02 RecSysFr #3
  6. 6. ● Interactive recommendation ● Understand user feedbacks Interactive Radios
  7. 7. Algorithms and Evaluation /03 RecSysFr #3
  8. 8. RecSysFr #3 Architecture overview Content data: - Tags - Popularity User data: - Taste model - Hot tracks - Behaviors Build tracklist - Data cache - User action history - Update user models - Consolidate tags data - Build indexes actions logs
  9. 9. RecSysFr #3 ● % users listening more than 10mn ● % users who reconnect more than 3 days last week ● % users who do a like / dislike => take care of statistical confidence ! A/B Tests evaluation metrics
  10. 10. ● A/B tests are costly, long ● Want to test more cases Offline testing: ● setup benchmarking methodology ● Freeze data and evaluate algos with user future actions RecSysFr #3 Offline testing / benchmarking
  11. 11. Offline Testing User Study AB Testing Candidates Best Offline Candidates Best User Studies Candidates Final choice 2013 - Shany, Gunawardana
  12. 12. Thanks for your attention Enjoy RecSysFr #3 @Deezer ! http://www.deezer.com/jobs

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