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A Modular Inference System for Probabilistic Description Logics

  • Giuseppe Cota
  • Fabrizio Riguzzi
  • Riccardo Zese
  • Elena Bellodi
  • Evelina Lamma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11142)

Abstract

While many systems exist for reasoning with Description Logics knowledge bases, very few of them are able to cope with uncertainty. BUNDLE is a reasoning system, exploiting an underlying non-probabilistic reasoner (Pellet), able to perform inference w.r.t. Probabilistic Description Logics. In this paper, we report on a new modular version of BUNDLE that can use other OWL (non-probabilistic) reasoners and various approaches to perform probabilistic inference. BUNDLE can now be used as a standalone desktop application or as a library in OWL API-based applications that need to reason over Probabilistic Description Logics. Due to the introduced modularity, BUNDLE performance now strongly depends on the method and OWL reasoner chosen to obtain the set of justifications. We provide an evaluation on several datasets as the inference settings vary.

Keywords

Probabilistic Description Logic Semantic Web Reasoner OWL Library 

Notes

Acknowledgement

This work was supported by the “GNCS-INdAM”.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Dipartimento di IngegneriaUniversity of FerraraFerraraItaly
  2. 2.Dipartimento di Matematica e InformaticaUniversity of FerraraFerraraItaly

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