Artificial Intelligence Group (Prof. Stuckenschmidt)

Our group conducts fundamental and applied research in knowledge representation formalisms with a focus on reasoning techniques for information extraction and integration. Our work is centered around:

  • Standard reasoning including description logic reasoning and non-standard reasoning techniques (explanations and debugging techniques)
  • Combining Probabilistic reasoning and Utility Theory with Description Logics
  • Applications in various domains (web data integration and management, semantic web, ontology matching, context-aware applications, Business Process Management etc.)  



Postdoctoral Researchers


PhD Students


  • Dr. Elena Beisswanger (2013): "Developing Ontological Background Knowledge for Biomedicine".
  • Dr. Arnab Dutta (2016): "Automated Knowledge Base Extension Using Open Information".
  • Dr. Rim Helaoui (2016): "On Leveraging Statistical and Relational Information for the Representation and Recognition of Complex Human Activities".
  • Prof. Dr. Kai Eckert (2012): "Usage-driven maintenance of knowledge organization systems".
  • Dr. Daniel Fleischhacker (2016): "Detecting Errors in Linked Data Using Ontology Learning and
    Outlier Detection".
  • Dr. Christian Meilicke (2011): "Alignment Incoherence in Ontology Matching".
  • Dr. Jan Noessner (2014): "Efficient Maximum A-Posteriori Inference in Markov Logic and Application in Description Logics".
  • Dr. Christoph Pinkel (2016): "Incremental, Interactive,Inter-Model Mapping Generation".
  • Dr. Anne Schlicht (2012): "Scaling Up Description Logic Reasoning by Distributed Resolution".
  • Dr. Caecilia Zirn (2016): "Fine-grained Position Analysis for Political Texts".

Selected Publications

Automated Decision Making:

  • Nico Potyka, Erman Acar, Matthias Thimm and Heiner Stuckenschmidt. Group decision making via probabilistic belief merging. In: Proceedings of 25th International Joint Conference on Artificial Intelligence (IJCAI '16), New York, USA, 9-15 July 2016, AAAI Press, New York, NY, 2016.
  • Erman Acar, Camilo Thorne and Heiner Stuckenschmidt. Towards Decision Making via Expressive Probabilistic Ontologies. In: Lecture Notes in Computer Science Algorithmic Decision Theory : 4th International Conference, ADT 2015, Lexington, KY, USA, September 27-30, 2015, Proceedings; 52-68. Springer, Cham, 2015.


Markov Logic Reasoning:


Activity Recognition:

Ontology Matching:


  • MWK Project: A Virtual Open Science Collaboration Environment
  • ZIM Project: A motio-visual Sensor System for Spare Part Logstics
  • DFG Project: Matching Representations at different Levels of Granularity
  • SFB 884: Political Economy of Reforms
  • Different Industry Projects

Software and Data

  • ALCOMO (a tool for repairing ontology alignments)
  • Rockit (a query engine for Markov Logic)
  • ELOG (a reasoner for log-linear description logics)
  • NELL2DBpedia (an evaluation gold standard for linking NELL entities to DBPedia instances)


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