Author: recsys-admin
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POI Recommender Systems for Customized Walking Tours Using Context and Category
Author: Joanna Zamiechowska Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb
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Enhancing Video Segment Discovery in Educational Content: A Conversational Approach with Retrieval-Augmented Generation
Author: Dragana Naceva Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Accessing information in educational video collections is not only a question of finding the right video, but also of locating the particular moment in which the relevant information is discussed. This becomes especially important for long-form recordings, where a user’s information need may correspond…
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The Role of Clarifying Questions in Conversational Recommender Systems: Balancing Explicitness
Author: Anna Baghumyan Supervisor: Julia Neidhardt, Co-Supervisor: Ahmadou Wagne
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Evaluating Agentic Retrieval Augmented Generation in Open Tender Evaluations
Author: Franz Ottitsch Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Public tender evaluation requires contracting authorities to assess bidder responses against defined award criteria across long, semi structured documents, a process that remains largely manual, time consuming and costly. Retrieval augmented generation (RAG) systems, particularly agentic variants with iterative retrieval and task decomposition, offer…
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Examining Tech Bias: Analyzing Career Recommendations in LLMs through Demographic Persona-Based Prompting
Supervisor: Julia Neidhardt, Co-Supervisor: Bernhard Krüpl-Sypien
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The Impact of Using Large Language Models on the Performance of Recommender Systems
Author: Michael Schmiedmayer Supervisor: Julia Neidhardt, Co-Supervisor: Ahmadou Wagne Abstract This thesis investigates the integration of Large Language Models (LLMs) into Conversational Recommender Systems (CRSs), evaluating the impact of model scale and hyperparameter configurations on retrieval performance. Moving beyond purely synthetic benchmarks, this research introduces a novel, end-to-end evaluation framework grounded in real-world user behaviour.…