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

    TextGraphs 2024 Shared Task on Text-Graph Representations for Knowledge Graph Question Answering

    Sakhovskiy, A., Salnikov, M., Nikishina, I., Usmanova, A., Kraft, A., Möller, C., Banerjee, D., Huang, J., Jiang, L., Abdullah, R., Yan, X., Ustalov, D., Tutubalina, E., Usbeck, R. & Panchenko, A., 01.08.2024, Proceedings of TextGraphs-17: Graph-based Methods for Natural Language Processing: Graph-Based Methods for Natural Language Processing, 62nd Annual Meeting of the Association of Computational Linguistics. Ustalov, D., Gao, Y., Pachenko, A., Tutubalina, E., Nikishina, I., Ramesh, A., Sakhovskiy, A., Usbeck, R., Penn, G. & Valentino, M. (eds.). Kerrville: Association for Computational Linguistics (ACL), p. 116-125 10 p.

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

  2. Published

    Understanding Environmental Posts: Sentiment and Emotion Analysis of Social Media Data

    Amangeldi, D., Usmanova, A. & Shamoi, P., 07.03.2024, In: IEEE Access. 12, p. 33504-33523 20 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

Previous 1 2 3 4 Next