Using Ontologies to Query Probabilistic Numerical Data

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10483)


We consider ontology-based query answering in a setting where some of the data are numerical and of a probabilistic nature, such as data obtained from uncertain sensor readings. The uncertainty for such numerical values can be more precisely represented by continuous probability distributions than by discrete probabilities for numerical facts concerning exact values. For this reason, we extend existing approaches using discrete probability distributions over facts by continuous probability distributions over numerical values. We determine the exact (data and combined) complexity of query answering in extensions of the well-known description logics \(\mathcal {EL}\) and \(\mathcal {ALC}\) with numerical comparison operators in this probabilistic setting.


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Theoretical Computer ScienceTechnische Universität DresdenDresdenGermany

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