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Recsys Challenge 2018 - Main Track

Team: cocoplaya


  • Andres Ferraro
  • Dmitry Bogdanov
  • Jason Yoon
  • Lucas Kim

Username in aferraro


In order to reproduce the recommendations submitted for the Main track of the challenge the file must be executed.

First we train a Matrix Factorization model and then we generate the recommendations based on this model to the playlists in the challenge_set, then we combine this results with other model which computes the most probable songs based on the coocurrence in the playlists. This is all computed in the file

To compute the Matrix Factorization we use the library LightFM, in requirements.txt you can find all the dependencies, we use the version 3.6.4 of Python. Inside you can specify where the MPD dataset is located and were the challenge_set is located. Also in this file you can specify where the output CSV should be placed.