A Framework for Reasoning on Probabilistic Description Logics
October 02, 2020 Β· Declared Dead Β· π Applications and Practices in Ontology Design, Extraction, and Reasoning
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Authors
Giuseppe Cota, Riccardo Zese, Elena Bellodi, Evelina Lamma, Fabrizio Riguzzi
arXiv ID
2010.01087
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.LO
Citations
1
Venue
Applications and Practices in Ontology Design, Extraction, and Reasoning
Last Checked
4 months ago
Abstract
While there exist several reasoners for Description Logics, very few of them can cope with uncertainty. BUNDLE is an inference framework that can exploit several OWL (non-probabilistic) reasoners to perform inference over Probabilistic Description Logics. In this chapter, we report the latest advances implemented in BUNDLE. In particular, BUNDLE can now interface with the reasoners of the TRILL system, thus providing a uniform method to execute probabilistic queries using different settings. BUNDLE can be easily extended and can be used either as a standalone desktop application or as a library in OWL API-based applications that need to reason over Probabilistic Description Logics. The reasoning performance heavily depends on the reasoner and method used to compute the probability. We provide a comparison of the different reasoning settings on several datasets.
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