MSc. N'Dah Jean KOUAGOU
Research Associate
My work is mostly about building efficient methods for (especially symbolic) machine learning on knowledge graphs. Current approaches for symbolic learning on knowledge graphs do not scale up to the sizes of modern knowledge graphs, which can easily reach billions of facts over millions of entities. My work hence includes but is not limited to devising novel learning approaches (e.g., new algorithms for class expression learning, refinement operators, etc) which are able to scale to large knowledge graphs.
- E-Mail:
- ndah.jean.kouagou@uni-paderborn.de
- nkouagou@aimsammi.org
- ORCID:
- 0000-0002-4217-897X
- Social Media:
- Office Address:
-
Technologiepark 6
33100 Paderborn - Room:
- TP6.3.310
- Office hours:
Monday - Friday
9 am - 5 pm
Publications
Latest Publications
N.J. KOUAGOU, C. Demir, H.M.A. Zahera, A. Wilke, S. Heindorf, J. Li, A.-C. Ngonga Ngomo, in: Companion Proceedings of the ACM on Web Conference 2024, ACM, 2024.
N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Springer International Publishing, 2023, pp. 209–226.
A.-C. Ngonga Ngomo, C. Demir, N.J. Kouagou, S. Heindorf, N. Karalis, A. Bigerl, in: Compendium of Neurosymbolic Artificial Intelligence, IOS Press, 2023, pp. 272–286.
N.J. Kouagou, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, Cham, 2023.
N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy, CEUR-WS, 2023.