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Dr. Daniel Obraczka

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  • Dr. Daniel Obraczka
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  • Daniel Obraczka
  • obraczka@informatik.uni-leipzig.de
  • +49 341 97 39516

About

  • 2018 - 2024 Researcher at ScaDS
  • Master of Science (Computer Science), University of Leipzig, October 2018
  • 2015 - 2018 Student Researcher at AKSW 

Research Interests

  • Knowledge Graphs
  • (Knowledge Graph) Embeddings
  • Data Integration
  • Machine Learning (especially for everything mentioned above)

PC Member

  • DI2KG 2020

Selected Talks

  • ScaDS.AI SummerSchool 2022: Connecting The Right Dots: Entity Resolution on Knowledge Graphs
  • DBpedia-Day colocated with SEMANTICS 2022: Fast Hubness-Reduced Nearest Neighbor Search for Entity Alignment in Knowledge Graphs

Betreute Abschlussarbeiten (5)

Jahr Typ Student Titel Status
2024 B. Sc. Luan de Paiva Orsini Optimizing Retrieval in a Graph RAG System Finished
2023 M. Sc. Steven Lehmann Link Prediction als Möglichkeit zur automatisierten Personaleinsatzplanung Finished
2022 B. Sc. Jonathan Weske Standzeitvorhersage innerhalb eines Fahrradverleihsystems Finished
2022 M. Sc. Duong Trung Duong Scalable and Accurate Decision Tree Learning for Entity Resolution Finished
2021 B. Sc. Tinsaye Abye TF-IDF for Entity Resolution in huge Knowledge Graphs Finished

Publications (13)

Dateien Cover Beschreibung Jahr
Comparing Symbolic and Embedding-Based Approaches for Relational Blocking
Obraczka, D. ; Rahm, E.
24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-24)
2024 / 11
Construction of Knowledge Graphs: Current State and Challenges
Hofer, M. ; Obraczka, D. ; Saeedi, A. ; Köpcke, H. ; Rahm, E.
Information
2024 / 8
Big Data Integration for Industry 4.0
Obraczka, D. ; Saeedi, A. ; Christen, V. ; Rahm, E.
Digital Transformation
2023 / 2
Construction of Knowledge Graphs: State and Challenges
Hofer, M. ; Obraczka, D. ; Saeedi, A. ; Köpcke, H. ; Rahm, E.
arXiv
2023 / 2
Fast Hubness-Reduced Nearest Neighbor Search for Entity Alignment in Knowledge Graphs
Obraczka, D. ; Rahm, E.
Springer Nature Computer Science Journal
2022 / 10
An Evaluation of Hubness Reduction Methods for Entity Alignment with Knowledge Graph Embeddings
Obraczka, D. ; Rahm, E.
Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (Best Student Paper Candidate)
2021 / 10
Embedding-Assisted Entity Resolution for Knowledge Graphs
Obraczka, D. ; Schuchart, J. ; Rahm, E.
Proc. ESWC workshop on Knowledge Graph Construction (KGCW), 2021
2021 / 6
LIMES: A Framework for Link Discovery on the Semantic Web
Ngomo, A. ; Sherif, M. ; Georgala, K. ; Hassan, M. ; Dreßler, K. ; Lyko, K. ; Obraczka, D. ; Soru, T.
KI - Künstliche Intelligenz, German Journal of Artificial Intelligence - Organ des Fachbereichs \"Künstliche Intelligenz\" der Gesellschaft für Informatik e.V.
2021 / 4
EAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs
Obraczka, D. ; Schuchart, J. ; Rahm, E.
Arxiv
2021 / 1
DBpedia FlexiFusion The Best of Wikipedia>Wikidata>Your Data
Frey, J. ; Hofer, M. ; Obraczka, D. ; Lehmann, J. ; Hellmann, S.
ISWC 2019
2019 / 10

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Recent publications

  • 2025 / 9: Generating Semantically Enriched Mobility Data from Travel Diaries
  • 2025 / 8: Slice it up: Unmasking User Identities in Smartwatch Health Data
  • 2025 / 7: MPGT: Multimodal Physics-Constrained Graph Transformer Learning for Hybrid Digital Twins
  • 2025 / 6: Leveraging foundation models and goal-dependent annotations for automated cell confluence assessment
  • 2025 / 6: SecUREmatch: Integrating Clerical Review in Privacy-Preserving Record Linkage

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