News
Stay updated on our lab’s latest activities and projects through our news section featuring insightful blogs.
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Hands-on Session AI @ AK-Tag
It was a pleasure for me to conduct a hands-on session on the possibilities, limitations, and challenges of AI at the AK-Tag 2024 [1] of the Federal Bureau of Anti-Corruption (BAK)! This showcase was created in collaboration with my colleague Ahmadou Wagne as part of our research in the Christian Doppler Laboratory for Recommender Systems.…
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Analysing Dynamics Over Time of Bias in Recommender Systems
Author: Boris Staykov Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Recommender systems play a pivotal role in personalizing user experiences across various domains such as e-commerce, news, and entertainment platforms. However, the presence of bias within these systems poses significant challenges, potentially leading to unfair treatment of users. This thesis addresses the critical issue…
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Evaluating the Fairness of News Recommender Algorithms Within Detected User Communities
Author: Bernhard Steindl Supervisor: Julia Neidhardt, Co-Supervisor: Mete Sertkan Abstract Recommender systems have become an essential part of our modern lives. Recommendation algorithms support users by recommending items tailored to their interests and by assisting in discovering new items. For example, some online news platforms use recommendation models to suggest news articles to users based…