Search results for "Description logic"

showing 10 items of 20 documents

Spatio-temporal Schema Integration with Validation: A Practical Approach

2005

We propose to enhance a schema integration process with a validation phase employing logic-based data models. In our methodology, we validate the source schemas against the data model; the inter-schema mappings are validated against the semantics of the data model and the syntax of the correspondence language. In this paper, we focus on how to employ a reasoning engine to validate spatio-temporal schemas and describe where the reasoning engine is plugged into our integration methodology. The validation phase distinguishes our integration methodology from other approaches. We shift the emphasis on automation from the a priori discovery to the a posteriori checking of the inter-schema mapping…

Data modelDescription logicComputer scienceData integritySchema (psychology)InformationSystems_DATABASEMANAGEMENTSemantic reasonerData miningLogic modelcomputer.software_genrecomputerComputer Science::DatabasesData modeling
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The complexity of finite model reasoning in description logics

2005

AbstractWe analyse the complexity of finite model reasoning in the description logic ALCQI, i.e., ALC augmented with qualifying number restrictions, inverse roles, and general TBoxes. It turns out that all relevant reasoning tasks such as concept satisfiability and ABox consistency are ExpTime-complete, regardless of whether the numbers in number restrictions are coded unarily or binarily. Thus, finite model reasoning with ALCQI is not harder than standard reasoning with ALCQI.

Deductive reasoningTheoretical computer scienceFinite satisfiabilityInverseLogic modelFinite satisfiabilitySatisfiabilityAboxDescription logicTheoretical Computer ScienceComputer Science ApplicationsConsistency (database systems)Number restrictionsTBox ALCQI-Konzept Beschreibungslogik EXPTIME-komplettDescription logicComputational Theory and Mathematicsddc:004TBox ALCQI-concept description logic EXPTIME-completeAlgorithmMathematicsInformation SystemsInformation and Computation
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Querying the Guarded Fragment with Transitivity

2016

We study the problem of answering a union of Boolean conjunctive queries q against a database Δ, and a logical theory φ which falls in the guarded fragment with transitive guards (GF + TG). We trace the frontier between decidability and undecidability of the problem under consideration. Surprisingly, we show that query answering under GF2 + TG, i.e., the two-variable fragment of GF + TG, is already undecidable (even without equality), whereas its monadic fragment is decidable; in fact, it is 2exptime-complete in combined complexity and coNP-complete in data complexity. We also show that for a restricted class of queries, query answering under GF+TG is decidable. © 2013 Springer-Verlag.

Discrete mathematicsClass (set theory)Transitive relationTrace (linear algebra)0102 computer and information sciences02 engineering and technology16. Peace & justice01 natural sciencesDecidabilityUndecidable problemTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESDescription logicFragment (logic)010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingConjunctive queryMathematicsAutomata, Languages, and Programming
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Counting in the Two Variable Guarded Logic with Transitivity

2005

We show that the extension of the two-variable guarded fragment with transitive guards (GF+TG) by functionality statements is undecidable. This gives immediately undecidability of the extension of GF+TG by counting quantifiers. The result is optimal, since both the three-variable fragment of the guarded fragment with counting quantifiers and the two-variable guarded fragment with transitivity are undecidable. We also show that the extension of GF+TG with functionality, where functional predicate letters appear in guards only, is decidable and of the same complexity as GF+TG. This fragment captures many expressive modal and description logics.

Discrete mathematicsTransitive relationGuarded logicTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESFragment (logic)Description logicFunctional predicateTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMSExtension (predicate logic)Undecidable problemMathematicsDecidability
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Connecting Granular and Topological Relations through Description Logics

2021

Granularity deals with organizing in greater or lesser detail data, information, and knowledge that resides at a granular level. This organization is carried out according to certain criteria, which thereby provide a context view or dimension also called granular perspective. Topological relations express spatial associations among geospatial features (points, polylines, and polygons); they represent a horizontal spatial analysis. The two domains allow scientists to conceive different perspectives of the world. In this article, we aim to combine the two representations through Description Logics (DL) rules to relate granular (vertical representation) and geospatial topological (horizontal r…

GeoSPARQL[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO]Topological RelationsGranular RelationsGranular ComputingDescription LogicGeospatial Data[INFO.INFO-FL] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL][MATH.MATH-GN] Mathematics [math]/General Topology [math.GN]
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On Using Conceptual Modeling for Ontologies

2004

Are database concepts and techniques suitable for ontology design and management? The question has been on the floor for some time already. It gets a new emphasis today, thanks to the focus on ontologies and ontology services due to the spread of web services as a new paradigm for information management. This paper analyzes some of the arguments that are relevant to the debate, in particular the question whether conceptual data models would adequately support the design and use of ontologies. It concludes suggesting a hybrid approach, combining databases and logic-based services.

Information managementComputer scienceNCCR-MICSmedia_common.quotation_subjectProcess ontologyNCCR-MICS/CL4Ontology (information science)computer.software_genreData modelingWorld Wide WebDescription logicData integrityConceptual modelOntologyInformation systemontologiesWeb servicecomputermedia_common
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Rough Pragmatic Description Logic

2013

In this chapter, a rough description logic is built on the basis of a pragmatic standpoint of representation of knowledge. The pragmatic standpoint has influenced the acceptance of a broader definition of the semantic network than that appearing in the literature. The definition of the semantic network is a motivation of the introduced semantics of the language of the descriptive logic. First, the theoretical framework of representation of knowledge that was proposed in the papers [24,25] is adjusted to the description of data processing. The pragmatic system of knowledge representation is determined, as well as situations of semantic adequacy and semantic inadequacy for represented knowled…

Interpretation (logic)Knowledge representation and reasoningbusiness.industrycomputer.software_genreSemanticsSemantic networkDescription logicFormal languageInformation systemRough setArtificial intelligencebusinesscomputerNatural language processingMathematics
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Pellet: A Practical OWL-DL Reasoner

2007

In this paper, we present a brief overview of Pellet: a complete OWL-DL reasoner with acceptable to very good performance, extensive middleware, and a number of unique features. Pellet is the first sound and complete OWL-DL reasoner with extensive support for reasoning with individuals (including nominal support and conjunctive query), user-defined datatypes, and debugging support for ontologies. It implements several extensions to OWL-DL including a combination formalism for OWL-DL ontologies, a non-monotonic operator, and preliminary support for OWL/Rule hybrid reasoning. Pellet is written in Java and is open source.

JavaComputer scienceProgramming languagemedia_common.quotation_subjectWeb Ontology LanguageSemantic reasonercomputer.software_genreOperator (computer programming)Description logicDebuggingMiddleware (distributed applications)Conjunctive querycomputermedia_commoncomputer.programming_languageSSRN Electronic Journal
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Ontology mapping specification in description logics for cooperative systems

2006

Le developpement rapide du Web semantique est lie a la specification de plus en plus d'ontologies. Celles-ci permettent de modeliser des connaissances agreees par des communautes de personnes concernant des domaines ou des tâches specifiques. Le meme domaine decrit par deux communautes distinctes sera modelise de facon differente. Les systemes cooperatifs visent a rendre les informations provenant de differentes sources disponibles au-dela de leurs divergences. Pour cela, ils doivent aligner, fusionner ou integrer ces ontologies. La decouverte de mappings est un point cle dans la resolution efficace des heterogeneites entre ontologies. Nous developpons une architecture qui connecte des syst…

Ontology (information science)computer.software_genre01 natural sciences030507 speech-language pathology & audiology03 medical and health sciencessemantic webDescription logic[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Semantic integrationontology0101 mathematicsSemantic Websimilarity estimationMathematicsInformation retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]business.industry010102 general mathematicsMappingsMappings ontologies web sémantique calcul de similarité estimation; Mappings ontology semantic web similarity estimation.[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Artificial intelligenceWeb service0305 other medical sciencebusinessMerge (version control)computer
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Modeling Changes for SHOIN(D) Ontologies: An Exhaustive Structural Model

2013

Ontology development starts with a rigorous ontological analysis that provides a conceptualization of the domain to model agreed by the community. An ontology, specified in a formal language, approximates the intended models of this conceptualization. It needs then to be revised and refined until an ontological commitment is found. Also ulterior updates, responding to changes in the domain and/or the conceptualization, are expected to occur throughout the ontology life cycle. To handle a consistent application of changes, a couple of ontology evolution methodologies have been proposed. Maintaining the structural consistency is one of the ontology evolution criteria. It implies modeling chan…

Ontology Inference Layer[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-WB] Computer Science [cs]/WebComputer scienceProcess ontology030303 biophysicsData_MISCELLANEOUS[ INFO.INFO-WB ] Computer Science [cs]/Web02 engineering and technologyOntology (information science)computer.software_genre03 medical and health sciencesOntology chart[INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]SHOIN(D) Description LogicOntology components0202 electrical engineering electronic engineering information engineeringUpper ontologyOWL DL[INFO.INFO-FL] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]0303 health sciencesbusiness.industryOntology-based data integration[INFO.INFO-WB]Computer Science [cs]/WebSuggested Upper Merged Ontology[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]Structural ConsistencyOntology EvolutionIEEE[ INFO.INFO-FL ] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]Ontology Model020201 artificial intelligence & image processing[ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO]Artificial intelligenceComputingMethodologies_GENERALChange ModellingbusinesscomputerNatural language processing
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