We hope that this re-release will enable further research and improvements in the field of music recommendation and automatic playlist continuation. The MSD Challenge has launched OctoWe release the Last. Most past works have approached this tasks in either a collaborative filtering like approach, where they ignore the content of the song and only use peoples usage patterns. For any model, to be able to identify top 10 songs from a set of 400 million is an extremely daunting task.

The Million Song Dataset Challenge (2012). There are over 400 million songs in the Million Playlist Dataset. The dataset and challenge will be available on an ongoing, open-ended basis, and allow for non-commercial, open research use. The Million Song Dataset Challenge 9 was a large scale, music recommendation chal- lenge, where the task was the one to predict which songs a user will listen. music recommendation challenge, where the goal is to predict the songs that a user will listen to. Today, we are very excited to announce that we have re-released the dataset and challenge on ! Since then, many researchers have contacted us to request the dataset be made available for ongoing research in music recommendation and machine learning. After the challenge was complete, the dataset and challenge website were taken down, with a summary of the challenge and winning entries published in the ACM Transactions on Intelligent Systems and Technology. The challenge ran from January to July 2018, and received 1,467 submissions from 410 teams. This represents the largest public dataset of music playlists in the world. As part of that challenge, we introduced The Million Playlist Dataset: a dataset of 1 million playlists consisting of over 2 million unique tracks by nearly 300,000 artists. In 2018, Spotify helped organize the RecSys Challenge 2018, a data science research challenge focused on music recommendation, specifically the task of automatic music playlist continuation.

Million song dataset challenge