Abstract
Ontology-based Data Access has intensively been studied as a very relevant problem in connection with semantic web data. Often it is assumed, that the accessed data behaves like a classical database, i.e. it is known which facts hold for certain. Many Web applications, especially those involving information extraction from text, have to deal with uncertainty about the truth of information. In this paper, we introduce an implementation and a benchmark of such a system on top of relational databases. Furthermore, we propose a novel benchmark for systems handling large probabilistic ontologies. We describe the benchmark design and show its characteristics based on the evaluation of our implementation.
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Notes
- 1.
In particular, axioms of the form \(A \sqsubseteq \exists R\) cannot be represented in ProbLog.
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The authors want to thank Christian Meilicke for his ongoing support and fruitful discussions about the topic of this paper.
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Schoenfisch, J., Stuckenschmidt, H. (2015). Towards Large-Scale Probabilistic OBDA. In: Beierle, C., Dekhtyar, A. (eds) Scalable Uncertainty Management. SUM 2015. Lecture Notes in Computer Science(), vol 9310. Springer, Cham. https://doi.org/10.1007/978-3-319-23540-0_8
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