Janna Omeliyanenko, M.Sc.
Chair of Data Science (Informatik X)
University of Würzburg
Campus Hubland Nord
Emil-Fischer-Straße 50
97074 Würzburg
Germany
Email: janna.omeliyanenko[at]uni-wuerzburg.de
Phone: (+49 931) 31 - 83384
Office: Room 50.03.018 (Building G50, Institutsgebäude Künstliche Intelligenz)
Projects and Research Interests
Knowledge Graph - Artificial Intelligence - Machine Learning - Natural Language Processing
Since the early 2019, I am part of the DMIR research group. As part of the NLP group, I am investigating approaches to combine structured knowledge representations such as knowledge graphs and unstructured knowledge representations such as language models to improve model performance.
Teaching
- NLP and Text Mining (winter term 2019/20, winter term 2021/22)
- Seminar "Selected Chapters from Machine Learning" (winter term 2020/21, summer term 2021, winter term 2021/22, summer term 2024)
- XtAI Lab I (winter term 2020/21, summer term 2021, winter term 2021/22, summer term 2022, winter term 2022/23, summer term 2023, winter term 2023/24)
- XtAI Lab II (summer term 2021, winter term 2022/23, summer term 2023, winter term 2023/24)
- Fundamentals of Algorithms and Data Structures (winter term 2022/23, winter term 2023/24)
Publications
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“PreAdapter: Pre-training Language Models on Knowledge Graphs”, International Semantic Web Conference ISWC 2024, to appear.(2024)
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“Large Language Models and Knowledge Graphs: Opportunities and Challenges”, Transactions on Graph Data and Knowledge, 1(1), 2:1–2:38, available: https://doi.org/10.4230/TGDK.1.1.2.(2023)
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“CapsKG: Enabling Continual Knowledge Integration in Language Models for Automatic Knowledge Graph Completion”, International Semantic Web Conference ISWC 2023.(2023)
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“Assessing Media Bias in Cross-Linguistic and Cross-National Populations”, Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 561–572, available: https://ojs.aaai.org/index.php/ICWSM/article/view/18084.(2021)
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“LM4KG: Improving Common Sense Knowledge Graphs with Language Models”, in International Semantic Web Conference, Springer.(2020)