@proceedings{DBLP:conf/dlog/2003handbook, editor = {F. Baader and D. Calvanese and D. L. McGuinness and D. Nardi and P. F. Patel-Schneider}, title = {The Description Logic Handbook: Theory, Implementation, and Applications}, booktitle = {Description Logic Handbook}, year = {2003}, publisher = {Cambridge University Press} } @incollection{dlchap, author={F. Baader and I. Horrocks and U. Sattler}, title={Description Logics}, booktitle={Handbook of knowledge representation}, year={2008}, publisher={Elsevier}, pages={135-179}, chapter={3}, } @article{DBLP:journals/ai/Schmidt-SchaussS91, author = {Manfred Schmidt-Schau{\ss} and Gert Smolka}, title = {Attributive Concept Descriptions with Complements}, journal = {Artif. Intell.}, volume = {48}, number = {1}, year = {1991}, pages = {1-26}, ee = {http://dx.doi.org/10.1016/0004-3702(91)90078-X}, bibsource = {DBLP, http://dblp.uni-trier.de} } @inproceedings{DBLP:conf/rweb/Straccia08, author = {Umberto Straccia}, title = {Managing Uncertainty and Vagueness in Description Logics, Logic Programs and Description Logic Programs}, booktitle = {International Summer School on Reasoning Web}, year = {2008}, pages = {54-103}, publisher={Springer}, series={LNCS}, volume={5224} } @article{DBLP:journals/ws/LukasiewiczS08, author = {T. Lukasiewicz and U. Straccia}, title = {Managing uncertainty and vagueness in description logics for the Semantic Web}, journal = {J. Web Sem.}, volume = {6}, number = {4}, year = {2008}, pages = {291-308}, } @inproceedings{DBLP:conf/iclp/Sato95, author = {T. Sato}, title = {A Statistical Learning Method for Logic Programs with Distribution Semantics}, booktitle = {ICLP}, year = {1995}, pages = {715-729}, publisher={MIT Press} } @article{DBLP:journals/jair/SatoK01, author = {Taisuke Sato and Yoshitaka Kameya}, title = {Parameter Learning of Logic Programs for Symbolic-Statistical Modeling}, journal = {J. Artif. Intell. Res.}, volume = {15}, year = {2001}, pages = {391-454}, } @article{Poo97-ArtInt-IJ, author = {D. Poole}, title = {The {I}ndependent {C}hoice {L}ogic for Modelling Multiple Agents under Uncertainty}, journal = {Artif. Intell.}, year = {1997}, volume = {94}, number = {1-2}, pages = {7-56}, publisher = {Elsevier Science Publishers Ltd.}, address = {Essex, UK} } @inproceedings{VenVer04-ICLP04-IC, author = {J. Vennekens and S. Verbaeten and M. Bruynooghe}, title = {Logic Programs With Annotated Disjunctions}, booktitle = {ICLP}, year = {2004}, volume={3131}, pages={195-209}, series={LNCS}, publisher={Springer}, } @inproceedings{DBLP:conf/ijcai/RaedtKT07, author = {De Raedt, L. and A. Kimmig and H. Toivonen}, title = {{ProbLog}: A Probabilistic {P}rolog and Its Application in Link Discovery.}, booktitle = {IJCAI}, year = {2007}, pages = {2462-2467}, } @inproceedings{RigBelLamZese12-URSW12, title = {Epistemic and Statistical Probabilistic Ontologies}, author = {Fabrizio Riguzzi and Evelina Lamma and Elena Bellodi and Riccardo Zese}, pages = { 3-14}, booktitle = { URSW}, series = {CEUR Workshop Proceedings}, volume = {900}, year = {2012}, publisher = {Sun {SITE} Central Europe} } @misc{ISWC03-tut, author={Patel-Schneider, P, F. and I. Horrocks and S. Bechhofer}, title={Tutorial on {OWL} }, booktitle={International Semantic Web Conference}, year={2003}, } @inproceedings{DBLP:conf/ijcai/SchlobachC03, author = {Stefan Schlobach and Ronald Cornet}, title = {Non-Standard Reasoning Services for the Debugging of Description Logic Terminologies}, booktitle = {IJCAI}, year = {2003}, pages = {355-362}, publisher = {Morgan Kaufmann}, } @phdthesis{Kalyanpurphd, author={Kalyanpur, A.}, title={Debugging and Repair of {OWL} Ontologies}, school={The Graduate School of the University of Maryland}, year={2006}, } @article{DBLP:journals/ws/KalyanpurPSH05, author = {A. Kalyanpur and B. Parsia and E. Sirin and J. A. Hendler}, title = {Debugging unsatisfiable classes in {OWL} ontologies}, journal = {J. Web Sem.}, volume = {3}, number = {4}, year = {2005}, pages = {268-293}, } @techreport{extended_tracing, title={Extending Tableau Tracing for {ABox} Updates}, author={C. Halaschek-Wiener and A. Kalyanpur and B. Parsia}, institution={University of Maryland}, year={2006}, } @inproceedings{DBLP:conf/semweb/KalyanpurPHS07, author = {A. Kalyanpur and B. Parsia and M. Horridge and E. Sirin}, title = {Finding All Justifications of {OWL DL} Entailments}, booktitle = {ISWC}, year = {2007}, pages = {267-280}, volume = {4825}, publisher = {Springer}, series = {LNCS} } @article{ZesBelRig16-AMAI-IJ, author = {Riccardo Zese and Elena Bellodi and Fabrizio Riguzzi and Giuseppe Cota and Evelina Lamma }, title = {Tableau Reasoning for Description Logics and its Extension to Probabilities}, journal = {Ann. Math. Artif. Intel.}, publisher = {Springer}, copyright = {Springer}, year = {2016}, pages = {1-30}, issn-print = {1012-2443}, issn-online = {1573-7470}, url = {http://dx.doi.org/10.1007/s10472-016-9529-3f}, pdf = {http://ds.ing.unife.it/~friguzzi/Papers/ZesBelRig-AMAI16.pdf}, doi = {10.1007/s10472-016-9529-3}, abstract = { The increasing popularity of the Semantic Web drove to a wide- spread adoption of Description Logics (DLs) for modeling real world domains. To help the diffusion of DLs, a large number of reasoning algorithms have been developed. Usually these algorithms are implemented in procedural languages such as Java or C++. Most of the reasoners exploit the tableau algorithm which features non-determinism, that is not easily handled by those languages. Prolog directly manages non-determinism, thus is a good candidate for dealing with the tableau's non-deterministic expansion rules. We present TRILL, for "Tableau Reasoner for descrIption Logics in pro- Log", that implements a tableau algorithm and is able to return explanations for queries and their corresponding probability, and TRILLP , for "TRILL powered by Pinpointing formulas", which is able to compute a Boolean for- mula representing the set of explanations for a query. Reasoning on real world domains also requires the capability of managing probabilistic and uncertain information. We show how TRILL and TRILLP can be used to compute the probability of queries to knowledge bases following DISPONTE semantics. Experiments comparing these with other systems show the feasibility of the approach.}, keywords = { Description Logics, Tableau, Prolog, Semantic Web}, scopus = {2-s2.0-84990986085} } @book{Zese17-SSW-BK, author = {Riccardo Zese}, title = {Probabilistic Semantic Web}, series = {Studies on the Semantic Web}, volume = {28}, publisher = {{IOS} Press}, year = {2017}, url = {http://ebooks.iospress.nl/volume/probabilistic-semantic-web-reasoning-and-learning}, doi = {10.3233/978-1-61499-734-4-i}, isbn = {978-1-61499-733-7} } @article{DBLP:journals/logcom/BaaderP10, author = {F. Baader and R. Pe{\~n}aloza}, title = {Axiom Pinpointing in General Tableaux}, journal = {Journal of Logic and Computation}, volume = {20}, number = {1}, year = {2010}, pages = {5-34}, ee = {http://dx.doi.org/10.1093/logcom/exn058}, bibsource = {DBLP, http://dblp.uni-trier.de} } @article{DBLP:journals/jar/BaaderP10, author = {F. Baader and R. Pe{\~n}aloza}, title = {Automata-Based Axiom Pinpointing}, journal = {Journal of Automated Reasoning}, volume = {45}, number = {2}, year = {2010}, pages = {91-129}, ee = {http://dx.doi.org/10.1007/s10817-010-9181-2}, bibsource = {DBLP, http://dblp.uni-trier.de} } @article{ZesBelCot19-TPLP-IJ, title = {Probabilistic {DL} Reasoning with Pinpointing Formulas: A Prolog-based Approach}, doi = {10.1017/S1471068418000480}, journal = {Theory and Practice of Logic Programming}, publisher = {Cambridge University Press}, copyright = {Cambridge University Press}, author = {Zese, Riccardo and Cota, Giuseppe and Lamma, Evelina and Bellodi, Elena and Riguzzi, Fabrizio}, pages = {449--476}, year = {2019}, volume = {19}, number = {3}, pdf = {https://arxiv.org/pdf/1809.06180.pdf}, scopus = {2-s2.0-85060024345}, doi = {10.1017/S1471068418000480} } @inproceedings{ZesBelLamRig13-CILC13-NC, title = {A Description Logics Tableau Reasoner in {Prolog}}, author = {Riccardo Zese and Elena Bellodi and Evelina Lamma and Fabrizio Riguzzi}, booktitle = {Proceedings of the 28th Italian Conference on Computational Logic ({CILC2013}), Catania, Italy, 25-27 September 2013}, editor = {Domenico Cantone and Marianna Nicolosi Asmundo}, year = {2013}, series = {CEUR Workshop Proceedings}, publisher = {Sun {SITE} Central Europe}, issn = {1613-0073}, number = {1068}, address = {Aachen, Germany}, pages = {33-47}, pdf = {http://ml.unife.it/wp-content/uploads/Papers/ZesBelLamRig-CILC13.pdf}, url = {http://ceur-ws.org/Vol-1068/paper-l02.pdf}, copyright = {by the authors} } @article{ZesBelCot18-TPLP-IJ, author = {Riccardo Zese and Elena Bellodi and Giuseppe Cota and Fabrizio Riguzzi and Evelina Lamma }, title = { Probabilistic {DL} Reasoning with Pinpointing Formulas: A {Prolog-based} Approach }, journal = TPLP_J, year = {2018}, pages={1--28}, publisher=CUP_P, DOI={10.1017/S1471068418000480}, pdf = {https://arxiv.org/pdf/1809.06180.pdf} } @article{RigBelLamZes15-SW-IJ, author={Fabrizio Riguzzi and Elena Bellodi and Evelina Lamma and Riccardo Zese}, title={Probabilistic Description Logics under the Distribution Semantics}, journal=SWIUA_J, volume={6}, number={5}, pages={447-501}, pdf = {http://ds.ing.unife.it/~friguzzi/Papers/RigBelLamZes-SW14.pdf}, year={2015}, doi={10.3233/SW-140154}, abstract={ Representing uncertain information is crucial for modeling real world domains. In this paper we present a technique for the integration of probabilistic information in Description Logics (DLs) that is based on the distribution semantics for probabilistic logic programs. In the resulting approach, that we called DISPONTE, the axioms of a probabilistic knowledge base (KB) can be annotated with a real number between 0 and 1. A probabilistic knowledge base then defines a probability distribution over regular KBs called worlds and the probability of a given query can be obtained from the joint distribution of the worlds and the query by marginalization. We present the algorithm BUNDLE for computing the probability of queries from DISPONTE KBs. The algorithm exploits an underlying DL reasoner, such as Pellet, that is able to return explanations for queries. The explanations are encoded in a Binary Decision Diagram from which the probability of the query is computed. The experimentation of BUNDLE shows that it can handle probabilistic KBs of realistic size. }, keywords={Probabilistic Ontologies, Probabilistic Description Logics, OWL, Probabilistic Logic Programming, Distribution Semantics}, }