Andrés Ferraro defends his PhD thesis
Title: Music Recommender Systems: Taking Into Account The Artists' Perspective
Supervisor: Xavier Serra
Jury: Emilia Gómez (UPF), Dr. Cynthia Liem (TU Delft), Dr. Óscar Celma (Spotify).
Abstract:
The contributions of this thesis are (i) identification of multiple aspects in which the current platforms and their recommender systems affect the music artists and concrete ways in which they could be more beneficial in the future, (ii) analysis of the algorithmic effect regarding gender imbalance in the recommendations and mitigation of such problem based on the output of artists’ interview, (iii) analysis of the longitudinal effect of multiple state-of-the-art algorithms for session-based recommendations in users behavior negatively affecting the artists, (iv) publication of the first large-scale open dataset that contains audio and playlist information, (iv) novel contrastive learning approach proposed to combine multiple modalities (audio, genre and playlist information) beneficial for multiple tasks such as music recommendation, genre classification and automatic-tagging.
It is necessary to improve recommender systems through multidisciplinary research. Contributions like the ones presented in this thesis allow us to move a step forward in that direction, making streaming platforms more beneficial for both the artists and users.
This thesis defense will take place online. To attend use this link (ID of the meeting 874 9835 0517). The microphone and camera must be turned off, and the online access will be unavailable after 30 minutes from the start of the defense.
Video: https://youtu.be/mbFIjM32ddc