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Frantisek Simancík

dblp:66/9856 · DBLP profile ↗
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7ranked-venue papers
2as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 6 · 2 first-authorTheory of computation · 2Databases, data management, data science and information retrieval · 1Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
4 papers
Knowledge representation and reasoning · 100%
Theoretical computer science
3 papers
Computational complexity · 63% Logic in computer science · 37%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
description logic
0.632016
Extending Consequence-Based Reasoning to SRIQ · KR 2016
Consequence-based and fixed-parameter tractable reasoning in description logics · Artif. Intell. 2014
Practical Reasoning with Nominals in the EL Family of Description Logics · KR 2012
Computational complexity › parameterized complexity
fixed-parameter tractability
0.212014
Consequence-based and fixed-parameter tractable reasoning in description logics · Artif. Intell. 2014
Knowledge, reasoning and agents › Knowledge representation and reasoning › description logic
nominals
0.112012
Practical Reasoning with Nominals in the EL Family of Description Logics · KR 2012
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology
ontology reasoning
0.112011
Consequence-Based Reasoning beyond Horn Ontologies · IJCAI 2011
Logic in computer science › knowledge representation and reasoning
description logic
0.122016
Extending Consequence-Based Reasoning to SRIQ · KR 2016
Consequence-Based Reasoning beyond Horn Ontologies · IJCAI 2011

Methods — techniques the papers use, named apart from their topics

consequence-based reasoning · 0.9fixed-parameter tractability · 0.4ordered resolution · 0.2
YearPublicationVenuePosition
2018 Consequence-Based Reasoning for Description Logics with Disjunctions and Number Restrictions
abstract
Classification of description logic (DL) ontologies is a key computational problem in modern data management applications, so considerable effort has been devoted to the development and optimisation of practical reasoning calculi. Consequence-based calculi combine ideas from hypertableau and resolution in a way that has proved very effective in practice. However, existing consequence-based calculi can handle either Horn DLs (which do not support disjunction) or DLs without number restrictions. In this paper, we overcome this important limitation and present the first consequence-based calculus for deciding concept subsumption in the DL ALCHIQ+. Our calculus runs in exponential time assuming unary coding of numbers, and on ELH ontologies it runs in polynomial time. The extension to disjunctions and number restrictions is technically involved: we capture the relevant consequences using first-order clauses, and our inference rules adapt paramodulation techniques from first-order theorem proving. By using a well-known preprocessing step, the calculus can also decide concept subsumptions in SRIQ---a rich DL that covers all features of OWL 2 DL apart from nominals and datatypes. We have implemented our calculus in a new reasoner called Sequoia. We present the architecture of our reasoner and discuss several novel and important implementation techniques such as clause indexing and redundancy elimination. Finally, we present the results of an extensive performance evaluation, which revealed Sequoia to be competitive with existing reasoners. Thus, the calculus and the techniques we present in this paper provide an important addition to the repertoire of practical implementation techniques for description logic reasoning.
Andrew Bate, Boris Motik, Bernardo Cuenca Grau, David Tena Cucala, Frantisek Simancík, Ian Horrocks 0001
J. Artif. Intell. Res.5
2016 Extending Consequence-Based Reasoning to SRIQ
Andrew Bate, Boris Motik, Bernardo Cuenca Grau, Frantisek Simancík, Ian Horrocks 0001
KR4
2014 Consequence-based and fixed-parameter tractable reasoning in description logics
Frantisek Simancík, Boris Motik, Ian Horrocks 0001
Artif. Intell.1
2014 The Incredible ELK - From Polynomial Procedures to Efficient Reasoning with ℰℒ Ontologies
Yevgeny Kazakov, Markus Krötzsch, Frantisek Simancík
J. Autom. Reason.3
2012 Practical Reasoning with Nominals in the EL Family of Description Logics
Yevgeny Kazakov, Markus Krötzsch, Frantisek Simancík
KR3
2011 Consequence-Based Reasoning beyond Horn Ontologies
abstract
Consequence-based ontology reasoning procedures have so far been known only for Horn ontology languages. A difficulty in extending such procedures is that non-Horn axioms seem to require reasoning by case, which causes non-determinism in tableau-based procedures. In this paper we present a consequence-based procedure for ALCH that overcomes this difficulty by using rules similar to ordered resolution to deal with disjunctive axioms in a deterministic way; it retains all the favourable attributes of existing consequence-based procedures, such as goal-directed “one pass ” classification, optimal worst-case complexity, and “pay-asyou-go” behaviour. Our preliminary empirical evaluation suggests that the procedure scales well to non-Horn ontologies. 1
Frantisek Simancík, Yevgeny Kazakov, Ian Horrocks 0001
IJCAI1
2011 Concurrent Classification of EL Ontologies
Yevgeny Kazakov, Markus Krötzsch, Frantisek Simancík
ISWC (1)3