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

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