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.

  1. 2025
  2. Published

    DBLPLink 2.0 -- An Entity Linker for the DBLP Scholarly Knowledge Graph

    Banerjee, D., Taffa, T. A. & Usbeck, R., 30.07.2025

    Research output: other publicationsOtherResearch

  3. 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/worksArticle in conference proceedingsResearchpeer-review

  4. 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/worksArticle in conference proceedingsResearchpeer-review

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