Category: Ongoing
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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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Data Transformation Tool to Explore News Recommenders
Author: Manuel Feuerstein Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract This thesis focuses on the development of a data transformation tool to analyze and leverage diverse data sources from Falter Verlagsgesellschaft m.b.H (Falter). Falter provides content-based data from platforms like falter.at and shop.falter.at, along with user-based data from Matomo Analytics and shop purchase statistics.…
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Advancing Session-Based Recommendations: Integrating Modern LLMs and Micro-Behaviors
Supervisor: Julia Neidhardt, Co-Supervisor: Ahmadou Wagne
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User Profiling with Graph Neural Networks: Assessing Fairness and Explainability
Supervisor: Julia Neidhardt
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Intent Discovery and Product Search for Price Comparison Sites
Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb