Abstract
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.
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Noessner, J., Niepert, M. (2011). ELOG: A Probabilistic Reasoner for OWL EL. In: Rudolph, S., Gutierrez, C. (eds) Web Reasoning and Rule Systems. RR 2011. Lecture Notes in Computer Science, vol 6902. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23580-1_25
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DOI: https://doi.org/10.1007/978-3-642-23580-1_25
Publisher Name: Springer, Berlin, Heidelberg
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