FaCT++ Description Logic Reasoner: System Description

By Dmitry Tsarkov, Ian Horrocks. International Joint Conference on Automated Reasoning, 2006

1,263 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/8a37e141ffbc3da67e153fd49daa314ea011f242

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Citations in the corpus

The MASTRO system for ontology-based data access (2011, methodology): “Differently from QuOnto, other well-known DL reasoners such as Racer [19], Pellet [32], and Fact++ [20] are essentially focused on standard ontology reasoning services (instance checking, ontology satisfiability, concept subsumption, etc.).”
HermiT: An OWL 2 Reasoner (2014, methodology): “A key novel idea in HermiT is the hypertableau calculus [30], which allows the reasoner to avoid some of the nondeterministic behaviour exhibited by the tableau calculus used in Pellet [36] and FaCT++ [39]—two other popular and widely used OWL reasoners.”
The OWL API: A Java API for OWL ontologies (2011, methodology): “The OWL API is used for loading and accessing ontologies and interfacing with the FaCT++ reasoner.”
Conjunctive Query Answering for the Description Logic SHIQ (2007, methodology): “Despite the high worst case complexity of the standard reasoning problems for very expressive DLs such as SHIQ , there are highly optimized implementations available, e.g., FaCT++ (Tsarkov & Horrocks, 2006), KAON2 1 , Pellet (Sirin, Parsia, Cuenca Grau, Kalyan-pur, & Katz, 2006), and RacerPro 2 .”
Integrating phenotype ontologies across multiple species (2010, positive): “We tried a variety of reasoning tools, including OWL-based reasoners such as Pellet, FaCT++ and HermiT [38-40].”
Ontology Matching (2007, methodology): “2007) or FaCT (Tsarkov and Horrocks 2006) to compute the final alignment in a way similar to what is presented in Sect.”
Semantic Image Interpretation - Integration of Numerical Data and Logical Knowledge for Cognitive Vision (2018, neutral): “These procedures are implemented in optimized tools called reasoners that are freely available, such as FaCT++ [105], HermiT [94], Pellet [96] and RacerPro [43].”
A Tableaux Decision Procedure for SHOIQ (2005, methodology): “…are no interactions between number restrictions, inverse roles and nominals, the rule will never be applied; in case there are no nominals, the new algorithm will behave like the algorithm for SHIQ; and in case there are no inverse roles, the new algorithm will behave like the algorithm for SHOQ.”
OWL 2: The next step for OWL (2008, methodology): “The standardization of OWL has sparked the development and/or adaption of a number of reasoners, including FacT++ [37], Pellet [32], RACER [11], and HermiT [26], and ontology editors, including Protégé 1 and Swoop [21].”