HermiT: A highly-efficient OWL reasoner. HermiT is reasoner for ontologies written using the Web Ontology Language (OWL). Given an OWL file, HermiT can determine whether or not the ontology is consistent, identify subsumption relationships between classes, and much more. HermiT is the first publicly-available OWL reasoner based on a novel “hypertableau” calculus which provides much more efficient reasoning than any previously-known algorithm. Ontologies which previously required minutes or hours to classify can often by classified in seconds by HermiT, and HermiT is the first reasoner able to classify a number of ontologies which had previously proven too complex for any available system to handle. HermiT uses direct semantics and passes all OWL 2 conformance tests for direct semantics reasoners.

References in zbMATH (referenced in 23 articles , 1 standard article )

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  1. Rodler, Patrick: Memory-limited model-based diagnosis (2022)
  2. Baader, Franz; Koopmann, Patrick; Kriegel, Francesco; Nuradiansyah, Adrian: Computing optimal repairs of quantified ABoxes w.r.t. static (\mathcalEL) TBoxes (2021)
  3. Cantone, Domenico; Nicolosi-Asmundo, Marianna; Santamaria, Daniele Francesco: An improved set-based reasoner for the description logic (\mathcalDL_\mathrmD^4,\times\dagger) (2021)
  4. Chen, Jiaoyan; Hu, Pan; Jimenez-Ruiz, Ernesto; Holter, Ole Magnus; Antonyrajah, Denvar; Horrocks, Ian: \textttOWL2Vec*: embedding of OWL ontologies (2021)
  5. Dubslaff, Clemens; Koopmann, Patrick; Turhan, Anni-Yasmin: Enhancing probabilistic model checking with ontologies (2021)
  6. Tena Cucala, David; Cuenca Grau, Bernardo; Horrocks, Ian: Pay-as-you-go consequence-based reasoning for the description logic (\mathcalSROIQ) (2021)
  7. Bhatia, M. P. S.; Kumar, Akshi; Beniwal, Rohit; Malik, Tushar: Ontology driven software development for automatic detection and updation of software requirement specifications (2020)
  8. Bonatti, Piero A.; Ioffredo, Luca; Petrova, Iliana M.; Sauro, Luigi; Siahaan, Ida R.: Real-time reasoning in OWL2 for GDPR compliance (2020)
  9. Cantone, Domenico; Nicolosi-Asmundo, Marianna; Santamaria, Daniele Francesco: A Set-theoretic approach to reasoning services for the description logic (\mathcalDL_D^4,\times) (2020)
  10. Calvanese, Diego; Montali, Marco; Dumas, Marlon; Maggi, Fabrizio M.: Semantic DMN: formalizing and reasoning about decisions in the presence of background knowledge (2019)
  11. Jiang, Yuncheng: A formal model of semantic computing (2019)
  12. Zese, Riccardo; Cota, Giuseppe; Lamma, Evelina; Bellodi, Elena; Riguzzi, Fabrizio: Probabilistic DL reasoning with pinpointing formulas: a Prolog-based approach (2019)
  13. Borgwardt, Stefan; Peñaloza, Rafael: Algorithms for reasoning in very expressive description logics under infinitely valued Gödel semantics (2017)
  14. Lopes, Carlos; Knorr, Matthias; Leite, João: Nohr: integrating XSB prolog with the OWL 2 profiles and beyond (2017)
  15. Parsia, Bijan; Matentzoglu, Nicolas; Gonçalves, Rafael S.; Glimm, Birte; Steigmiller, Andreas: The OWL reasoner evaluation (ORE) 2015 competition report (2017)
  16. Sikos, Leslie F.: Description logics in multimedia reasoning (2017)
  17. Zhou, Yujiao; Grau, Bernardo Cuenca; Nenov, Yavor; Kaminski, Mark; Horrocks, Ian: PAGOdA: pay-as-you-go ontology query answering using a datalog reasoner (2015)
  18. Glimm, Birte; Horrocks, Ian; Motik, Boris; Stoilos, Giorgos; Wang, Zhe: HermiT: an OWL 2 reasoner (2014)
  19. Nikitina, Nadeschda; Rudolph, Sebastian: (Non-)succinctness of uniform interpolants of general terminologies in the description logic (\mathcalEL) (2014)
  20. Zhang, Xiaowang; Xiao, Guohui; Lin, Zuoquan; Van den Bussche, Jan: Inconsistency-tolerant reasoning with OWL DL (2014)

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