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README.md

Recsys Challenge 2018 - Creative Track

This work is part of a collaboration between the Music Techology Group and Kakao Corp, under the supervision of Xavier Serra.

Team: cocoplaya

Members:

  • Andres Ferraro (MTG)
  • Dmitry Bogdanov (MTG)
  • Jason Yoon (Kakao Corp)
  • Lucas Kim (Kakao Corp)

Username in recsys-challenge.spotify.com: aferraro

contact: andres.ferraro at upf.edu

Instructions

In order to reproduce the recommendations submitted for the Creative track of the challenge the following steps must be executed:

  • Step 1: Download audio samples of the songs from spotify
  • Step 2: Compute features from the audio of the songs
  • Step 3: Train Matrix Factorization model and generate recommendations, merge with reccomendations generated from songs co-ocurrence probabilities.

The code to reproduce each step is contained in a separate folder, you can find further instructions inside the folders.

Citations

For citations you can reference this paper::

Ferraro, A., Bogdanov, D., Yoon, J., Kim, K., & Serra, X. (2018, October). "Automatic playlist continuation using a hybrid recommender system combining features from text and audio". In Proceedings of the ACM Recommender Systems Challenge 2018 (p. 2). ACM.

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Spotify RecSys Challenge 2018 creative track: team 'cocoplaya'

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