Maschinelles Lernen

Big Data

Programmiermethoden und Programmiertechnik

MINTFIT Hamburg

Forschungsprojekte:

• Forum 4.0 im Rahmen von Ahoi.Digital (abgeschlossen)

Mitgliedschaften:

• Association for Computational Linguistics (ACL)

2022

• Barbas, H., Soll, M., Andersen, J. S., Bender, E., Hamann, F., Haustermann, H., & Sitzmann, D. (2022). The MINTFIT Computer Science Online Course. In IEEE German Education Conference 2022 (GeCon) (Forthcoming). IEEE.
• Andersen, J. S., & Maalej, W. (2022). Efficient, Uncertainty-based Moderation of Neural Networks Text Classifiers. In Findings of the Association for Computational Linguistics (ACL) (pp. 1536-1546).
• Andersen, J. S., & Zukunft, O. (2022). Towards More Reliable Text Classification on Edge Devices via a Human-in-the-Loop. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART)  (pp. 636-646).

2021

• Andersen, J. S., Zukunft, O., & Maalej, W. (2021). REM: Efficient Semi-Automated Real-Time Moderation of Online Forums. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations (ACL-IJCNLP) (pp. 142-149).
• Haering, M., Andersen, J. S., Biemann, C., Loosen, W., Milde, B., Pietz, T., Stoecker, C., Wiedemann, G., Zukunft, O., & Maalej, W. (2021). Forum 4.0: An Open-Source User Comment Analysis Framework.  In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations (EACL) (pp. 63-70).

2020

• Andersen, J. S., Schöner, T., & Maalej, W. (2020). Word-Level Uncertainty Estimation for Black-Box Text Classifiers using RNNs. In Proceedings of the 28th International Conference on Computational Linguistics (COLING) (pp. 5541-5546).

2019

• Tropmann-Frick, M., & Andersen, J. S. (2019). Towards Visual Data Science-An Exploration. In Proceedings of the International Conference on Human Interaction and Emerging Technologies (IHIET) (pp. 371-377). Springer.
• Andersen, J. S. (2019). A User Centric Visual Analytics Framework for News Discussions. In Proceedings of the Workshops of the EDBT/ICDT 2019 Joint Conference.

2016

• Andersen, J. S., & Zukunft, O. (2016). Semi-Clustering that Scales: an Empirical Evaluation of GraphX. In 2016 IEEE International Congress on Big Data (BigData Congress) (pp. 333-336). IEEE.
• Andersen, J. S., & Zukunft, O. (2016). Evaluating the Scaling of Graph-Algorithms for Big Data using GraphX. In 2016 2nd International Conference on Open and Big Data (OBD) (pp. 1-8). IEEE.

Publikationsliste auf dblp.org