Recommender Systems

Strategies for mitigating artist gender bias in music recommendation: a simulation study
Recommender systems are prone to various biases. Hence, bias mitigation approaches are needed to counteract those. In the music sector, …
PDF Cite DOI
Third workshop: perspectives on the evaluation of recommender systems (PERSPECTIVES 2023)
Evaluation is important when developing and deploying recommender systems. The PERSPECTIVES workshop sheds light on the different, …
PDF Cite DOI ACM Author-izer CORE 2023: A GGS 2021: A
Keynote: Keep an eye on the big picture—in recommender systems research and as a scientist
Keynote at Women in RecSys 2023.
30 August 2023
Slides
Keynote: Keep an eye on the big picture—in recommender systems research and as a scientist
Three views of a secret: embracing multiple perspectives in the evaluation of information retrieval and recommender systems
As users are increasingly confronted with information and choice overload, we need the ‘right’ information, at the …
PDF Cite
Musikempfehlungssysteme aus der Perspektive von Artists: Was ist fair?
Talk at the Symposion Musik & Mathematik.
2 June 2023
Program
Musikempfehlungssysteme aus der Perspektive von Artists: Was ist fair?
Keynote: K.I. in der Musikbranche: Last oder Lösung?—Ethische Fragen im Zusammenhang mit Algorithmen
Keynote at Future Music Camp 2023.
25 May 2023
Video Program
Keynote: K.I. in der Musikbranche: Last oder Lösung?—Ethische Fragen im Zusammenhang mit Algorithmen