ELOG: A Probabilistic Reasoner for OWL EL

  • Jan Noessner
  • Mathias Niepert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6902)


Log-linear description logics are probabilistic logics combining several concepts and methods from the areas of knowledge representation and reasoning and statistical relational AI. We describe some of the implementation details of the log-linear reasoner ELOG. The reasoner employs database technology to dynamically transform inference problems to integer linear programs (ILP). In order to lower the size of the ILPs and reduce the complexity we employ a form of cutting plane inference during reasoning.


Integer Linear Program Description Logic Conjunctive Query Ground Atom Markov Logic Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jan Noessner
    • 1
  • Mathias Niepert
    • 1
  1. 1.KR & KM Research GroupUniversität MannheimMannheimGermany

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