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. Published

    Analyzing the Influence of Knowledge Graph Information on Relation Extraction

    Möller, C. & Usbeck, R., 2025, The Semantic Web: 22nd European Semantic Web Conference, ESWC 2025 Portoroz, Slovenia, June 1–5, 2025 Proceedings, Part I. Curry, E., Acosta, M., Poveda-Villalón, M., van Erp, M., Ojo, A., Hose, K., Shimizu, C. & Lisena, P. (eds.). Cham: Springer Nature Switzerland AG, Vol. 1. p. 460-480 21 p. (Lecture Notes in Computer Science ; vol. 15718).

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

  2. Published

    Analyse von Mikro-Blog-Daten

    Usbeck, R., 2013, Informatiktage 2013 - Fachwissenschaftlicher Informatik-Kongress, 22. und 23. März 2013. Gesellschaft für Informatik e.V., p. 165-168 4 p. (Lecture Notes in Informatics (LNI); vol. S12).

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearch

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