Recommendation @Deezer

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  • RecSysFr #3Recommendation @Deezer

    RecSysFr, Paris, 2016 June 22th

    B. Mathieu, Head of Data Science

  • Deezer

    /01

    RecSysFr #3

  • Deezer overview

    RecSysFr #3

    420 employees in 20 cities 5M albums 40M tracks 100M playlists

    16M MAU 6M subscribers

  • ~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

  • Recommendation opportunities

    /02

    RecSysFr #3

  • Interactive recommendation

    Understand user feedbacks

    Interactive Radios

  • Algorithms and Evaluation

    /03

    RecSysFr #3

  • 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

  • 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

  • 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

  • Offline Testing

    User Study

    AB Testing

    Candidates Best Offline Candidates

    Best User Studies Candidates

    Final choice

    2013 - Shany, Gunawardana

  • Thanks for your attention

    Enjoy RecSysFr #3 @Deezer !

    http://www.deezer.com/jobs

    https://www.deezer.com/company/jobshttps://www.deezer.com/company/jobs