{"id":2,"date":"2023-02-18T14:41:30","date_gmt":"2023-02-18T13:41:30","guid":{"rendered":"http:\/\/colda.uol.de\/?page_id=2"},"modified":"2025-11-20T11:31:45","modified_gmt":"2025-11-20T10:31:45","slug":"publikationen","status":"publish","type":"page","link":"https:\/\/colda.uol.de\/en\/publikationen\/","title":{"rendered":"Publications"},"content":{"rendered":"

G. Schumann, J. Awick, and J. Marx G\u00f3mez. (2023). Natural Language Processing using Federated Learning: A Structured Literature Review. In Proc. 2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings)<\/em>, 2023
doi: 10.1109\/AIBThings58340.2023.10292481 <\/span><\/a><\/a><\/p>\n\n\n\n

J. P. Awick, G. Schumann, & J. Marx G\u00f3mez. (2023, November). Exploring Federated Learning for Data Integration: A Structured Literature Review.In 2023International Conference on Big Data, Knowledge and Control Systems Engineering (BdKCSE) (pp. 1-8). IEEE. doi: 10.1109\/BdKCSE59280.2023.10339771 <\/a><\/a><\/p>\n\n\n\n

G. Schumann, and J. Marx G\u00f3mez. (2024, September). Detection of conflicts, contradictions and inconsistencies in regulatory documents: a literature review. In 2024 Fifth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)<\/em> (pp. 81-88). IEEE. doi: 10.1109\/IDSTA62194.2024.10747003 <\/a><\/a><\/p>\n\n\n\n

J. P. Awick, L. Steffens, M. Karl, and J. Marx G\u00f3mez. (2024, December). A Taxonomy for Evaluating Data Quality in Data Integration-Towards a Standardized Data Quality Management. In 2024 IEEE International Conference on Data Science and Systems (DSS) (pp.15-25). IEEE.<\/p>\n\n\n\n

J. P. Awick. (2025, April). Benchmarking Scalability and Effectiveness of Blocking Approaches for Entity Matching: A Comparative Analysis. In 2025 10th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA)<\/em> (pp. 512-521). IEEE. doi: 10.1109\/ICCCBDA64898.2025.11030486<\/a><\/p>\n\n\n\n

S. Rudolph, G. Schumann, L. Steffens, M. Karl and J. Marx G\u00f3mez (2025). Highly scaled Federated Learning Simulations for Text Classification. In Proceedings of the 10th<\/em> International Conference on Computer and Communication Systems 2025, Chengdu, China, IEEE, 2025. doi: 10.1109\/ICCCS65393.2025.11069933<\/a><\/p>\n\n\n\n

\n\n\n\n

Angenommene Publikationen<\/strong><\/p>\n\n\n\n

G. Schumann, Contradictions and Inconsistencies in Regulatory Documents \u2013 A qualitative Assessment from Practice (2025). In 2025 15th International Conference on Advanced Computer Information Technologies (ACIT), IEEE.<\/p>\n\n\n\n

C. Montag, G. Schumann, L. Steffens, M. Karl and J. M. G\u00f3mez, Decentralized Federated Learning using Transformer-based Language Models. In 2025 1st International Conference on Recent Advances in Information Systems (ICRAIS), Springer.<\/p>\n\n\n\n

J. P. Awick, and J. Marx G\u00f3mez. Entity Matching in the Era of Language Models: A Structured Literature Review (2025). In 2025 25th International Conference on Control Systems and Computer Science (CSCS). IEEE.<\/p>\n\n\n\n

J. Boekhoff, J. P. Awick, and J. Marx G\u00f3mez, (2025, September). A Comprehensive Comparison of Federated Learning Frameworks (2025). In 2025 1st International Conference on Recent Advances in Information Systems (ICRAIS), Springer.<\/p>\n\n\n\n

Betreute Abschlussarbeiten<\/strong><\/p>\n\n\n\n

Titel<\/td>Betreut durch<\/td>Bachelor-\/Masterarbeit<\/td><\/tr>
Einsatzpotenziale von Federated Learning im Record-Linkage-Prozess<\/td>Jap-Philipp Awick<\/td>Masterarbeit<\/td><\/tr>
Vergleich von Federated Learning Frameworks<\/td>Jap-Philipp Awick<\/td>Bachelorarbeit<\/td><\/tr>
Decentralized Federated Contradiction Detection<\/td>Gerrit Schuhmann<\/td>Masterarbeit<\/td><\/tr>
Federated Contradiction Detection<\/td>Gerrit Schuhmann<\/td>Masterarbeit<\/td><\/tr>
Normgerechte Datenqualit\u00e4tsreports f\u00fcr KI<\/td>Gerrit Schuhmann<\/td>Bachelorarbeit<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

<\/p>","protected":false},"excerpt":{"rendered":"

G. Schumann, J. Awick, and J. Marx G\u00f3mez. (2023). Natural Language Processing using Federated Learning: A Structured Literature Review. In Proc. 2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings), 2023doi: 10.1109\/AIBThings58340.2023.10292481 J. P. Awick, G. Schumann, & J. Marx G\u00f3mez. (2023, November). Exploring Federated Learning for Data Integration: A Structured Literature Review.In … <\/p>\n

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