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