Tag: Machine Learning
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Data-Centric AI for Conceptual Modeling: Cleansed Data and GNN-LLM based Recommender for UML Class Diagrams
Author: Andjela Djelic Supervisor: Dominik Bork, Co-Supervisor: Julia Neidhardt Abstract In the Model-Driven Engineering (MDE) domain, Machine Learning (ML)-based recommender systems can assist developers during conceptual modeling by suggesting plausible modeling elements based on the current state of a model. However, the conceptual model datasets commonly used for such machine learning research, often mined from…
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Content-Based Restaurant Recommendation Systems Using Textual and Visual Data
Author: Dante Godolja Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Content-based restaurant recommender systems use features such as cuisine type, price range, and location to suggest dining options to users. By analyzing the content of restaurants, these systems can generate recommendations. Current research explores ways to improve their effectiveness. In this thesis we explore…
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COVID-19 and Populism in Austrian News User Comments – A Machine Learning Approach
Author: Ahmadou Wagne Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract The COVID-19 pandemic and the resulting government measures have triggered a wave of protests and demonstrations in Austria. We saw some protestors resorting to populist rhetoric to express their dissatisfaction, which in some cases, led to anti-democratic tendencies. Populist talking points have not been…
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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…
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Dynamic Sentiment Analysis for Measuring Media Bias
Author: Thomas E. Kolb Supervisor: Julia Neidhardt, Co-Supervisor: Hannes Werthner Abstract Analyzing the sentiments of texts in the field of social news and news media is a big area of interest for many researchers around the world. It is a well-known problem to “teach” machines to understand the sentiments of texts e.g. news media. This…