Datasets from the KDD 2021 article "A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps"

We publicly release the anonymized <em>song_embeddings.parquet user_embeddings.parquet user_features_test.parquet user_features_train.parquet user_features_validation.parquet</em> datasets, with each of the TT-SVD or UT-ALS versions of embeddings, from the music streaming platform Deezer, as described in the article "<em>A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps"</em> published in the proceedings of the 27TH ACM SIGKDD conference on knowledge discovery and data mining (<em>KDD 2021</em>). The paper is available here. These datasets are used in the GitHub repository deezer/semi_perso_user_cold_start to reproduce experiments from the article. Please cite our paper if you use our code or data in your work.