Tag: RecommenderSystems
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Integrating Local Knowledge and Large Language Models: New Paper Accepted at the Knowledge-aware and Conversational Recommender Systems Workshop at the RecSys’23
📢 Exciting News! 📚 Our paper titled “Potentials of Combining Local Knowledge and LLMs for Recommender Systems” has been accepted at the 5th Knowledge-aware and Conversational Recommender Systems Workshop. 🌐 Language Models have reshaped the landscape of natural language understanding, opening up new avenues for improving recommendation systems. In this work, we explore how combining…
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Exploring Group Fairness in News Media Recommendations: Algorithms, Metrics, and Grouping
Author: Blake Huebner Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Beyond accuracy metrics, such as fairness and diversity, have become widely studied topics in recommender systems. Improving these metrics is important not only from an ethical and legal perspective, but can also improve overall user satisfaction. Although fairness and diversity metrics are widely discussed,…
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Exhibit Rating Prediction and Visitor Path Prediction in a Museum Setting
Author: Marek Furka Supervisor: Julia Neidhardt Abstract Rating prediction and path prediction tasks in a museum/exhibition setting are important problems, yet not well explored. Existing literature is limited and authors rarely compare multiple approaches, leaving an apparent research gap. In this study, we aim to close this research gap by giving a comprehensive comparison of…