Recommender Systems

The challenge of understanding explanations for user trust in AI: Insights from an experiment about job matching
Artificial Intelligence (AI) is widely used in recruitment with Job Recommender Systems (JRS) being designed for job matching. However, …
Glenda Hannibal, Christine Bauer
Cite DOI CORE 2023: B GGS 2021: B
Beyond Algorithms: Reclaiming the Interdisciplinary Roots of Recommender Systems (BEYOND 2025)
Workshop on Beyond Algorithms: Reclaiming the Interdisciplinary Roots of Recommender Systems (BEYOND 2025), co-located with RecSys 2025.
Eva Zangerle, Alan Said, Christine Bauer
26 September 2025 Event
DOI
Beyond Algorithms: Reclaiming the Interdisciplinary Roots of Recommender Systems (BEYOND 2025)
Beyond Algorithms: Reclaiming the Interdisciplinary Roots of Recommender Systems (BEYOND 2025)
This workshop challenges the machine learning-centric focus of modern recommender systems research by reconnecting the field with its …
Eva Zangerle, Alan Said, Christine Bauer
PDF Cite DOI ACM Author-izer CORE 2023: A GGS 2021: A
Why Do Recommenders Recommend? Three Waves of Research Perspectives on Recommender Systems
Research on Recommender Systems (RSs) has evolved across disciplines, from a focus on technical optimization to a broader interest in …
Annelien Smets, Christine Bauer
Cite
3rd Music Recommender Systems Workshop (MuRS 2025)
3rd Music Recommender Systems Workshop (MuRS 2025), co-located with RecSys 2025.
Andrés Ferraro, Lorenzo Porcaro, Christine Bauer
22 September 2025 Event
DOI
3rd Music Recommender Systems Workshop (MuRS 2025)
MuRS: 3rd Music Recommender Systems Workshop
Music recommendation has been a core area of interest within the recommender systems community since its early days. With the rise of …
Andres Ferraro, Lorenzo Porcaro, Christine Bauer
PDF Cite DOI ACM Author-izer CORE 2023: A GGS 2021: A
CfP for ECIR 2026
The CfPs for ECIR 2026 are available online.
24 August 2025 1 min read News
CfP for ECIR 2026
You can’t always get what you want: When algorithms try but biases persist
Invited talk for a DAS Lecture at the University of Salzburg.
Christine Bauer
6 May 2025
You can’t always get what you want: When algorithms try but biases persist
Fair Play? Mitigating bias in music recommender systems
Invited talk at the HCI Lecture Series at the University of Salzburg.
Christine Bauer
23 April 2025
Project
Wie arbeiten digitale Empfehlungssysteme?
Science talk for kids & teens.
22 April 2025
Flyer
Wie arbeiten digitale Empfehlungssysteme?