Recommender Systems
Andrés Ferraro will present our joint paper at CHIIR 2021. In the paper with the title Break the Loop: Gender Imbalance in Music Recommenders, we investigate the imbalance in music recommendations with respect to the artists gender. We propose a simple re-ranking approach to mitigate the problem and show in a simulation of feedback loops how the gender (im-)balances evolves over time.
I am looking forward to give a tutorial on Multi-method evaluation of adaptive systems: Why and how? at UMAP 2021.
PDF Cite Project Slides DOI ACM Author-izer ICORE 2026: A GGS 2021: B
The videos of all ComplexRec 2020 workshop talks at RecSys 2020—including my keynote—can now be found on the RecSys YouTube channel.
I am looking forward to join the panel on gender bias and discrimination in AI at the VUT Indie Days 2020 tomorrow. The panel is scheduled for 13:15 CEST and will be streamed on c/o pop xoxo in channel 1. Although originally planned to be held in English, the discussion will be in German. Maybe a good reason to brush up your German skills ;-)
My interview for LIWEST Kundenmagazin, Ausgabe Juli 2020 (pdf, e-paper) was recorded.
A 10 minutes cut of this interview is now online as a video on YouTube.
Cooperation of LIWEST und dorf tv. Topic: Wie wissen Online-Plattformen wie Spotify & Co, welche Musik ihren Nutzern gefällt? (How do online platforms such as Spotify know what music its users like?). Interviewer: Christian Naderer. Camera and cut: Roland Freinschlag.