author = {Federico Chesani and
               Giuseppe Cota and
               Marco Gavanelli and
               Evelina Lamma and
               Paola Mello and
               Fabrizio Riguzzi},
  title = {Declarative and Mathematical Programming approaches to Decision Support
               Systems for food recycling},
  journal = {Engineering Applications of Artificial Intelligence},
  volume = {95},
  pages = {103861},
  year = {2020},
  doi = {10.1016/j.engappai.2020.103861},
  scopus = {2-s2.0-85089188550}
  author = {Losi, Enzo and Venturini, Mauro and Manservigi, Lucrezia and Ceschini, Giuseppe Fabio and Bechini, Giovanni and Cota, Giuseppe and Riguzzi, Fabrizio},
  title = {Structured Methodology for Clustering Gas Turbine Transients by means of Multi-variate Time Series},
  year = {2020},
  publisher = {ASME},
  booktitle = {Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. Virtual, Online. September 21–25, 2020.},
  pages = {V009T21A005},
  doi = {10.1115/GT2020-14751},
  volume = {9}
  title = {A Framework for Reasoning on Probabilistic Description Logics},
  author = {Cota, Giuseppe and Zese, Riccardo and Bellodi, Elena and Lamma, Evelina and Riguzzi, Fabrizio},
  booktitle = {Applications and Practices in Ontology Design, Extraction, and Reasoning},
  series = {Studies on the Semantic Web},
  volume = {49},
  editor = {Cota, Giuseppe and Daquino, Marilena and Pozzato, Gian Luca},
  isbn = {978-1-64368-142-9},
  doi = {10.3233/SSW200040},
  language = {English},
  pages = {127-144},
  year = {2020},
  publisher = {{IOS} Press},
  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.
  copyright = {Akademische Verlagsgesellschaft AKA GmbH, Berlin}

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