Professorship for Information Systems, in particular Artificial Intelligence and Explainability
Organisational unit: Professoship
Organisation profile
The research group on Artificial Intelligence and Explainability focuses on hybrid AI methods to make machines understand human-created data. That is, we combine modern, sub-symbolic machine learning approaches with symbolic knowledge engineering based on Knowledge Graphs to develop transparent AI systems. We focus on Knowledge Extraction, Speech Assistants, Question Answering, AI ethics, and more.
41 - 43 out of 43Page size: 10
- 2025
 - Published
DBLPLink 2.0 -- An Entity Linker for the DBLP Scholarly Knowledge Graph
Banerjee, D., Taffa, T. A. & Usbeck, R., 30.07.2025Research output: other publications › Other › Research
 - Published
HySQA: Hybrid Scholarly Question Answering
Taffa, T., Banerjee, D., Assabie, Y. & Usbeck, R., 26.08.2025, Linking Meaning: Semantic Technologies Shaping the Future of AI: Proceedings of the 21st International Conference on Semantic Systems, 3-5 September 2025, Vienna, Austria. Spahiu, B., Vahdati, S., Salatino, A., Pellegrini, T. & Havur, G. (eds.). Amsterdam: IOS Press BV, p. 247-263 17 p. (Studies on the Semantic Web; vol. 62).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
 - Published
ASK-DBLP: Answering Questions over DBLP
Taffa, T., Neises, P., Ollinger, S., Westphal, P., Ackermann, M. R., Banerjee, D. & Usbeck, R., 02.11.2025, Joint Proceedings of Industry, Doctoral Consortium, Posters and Demos of the 24th International Semantic Web Conference (ISWC-C 2025). Vol. Vol-4085.Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
 
