Uses of Class org.dllearner.core.owl.Description (DL-Learner Javadoc)

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Uses of Class
org.dllearner.core.owl.Description

Packages that use Description
org.dllearner.algorithms	Learning Algorithms.
org.dllearner.algorithms.celoe
org.dllearner.algorithms.el	Learning algorithms for the EL description logic.
org.dllearner.algorithms.fuzzydll
org.dllearner.algorithms.gp	Genetic Programming Learning Algorithm.
org.dllearner.algorithms.hybridgp	Hybrid Learning Algorithm: A combination of Genetic Programming and Refinement Operators.
org.dllearner.algorithms.isle
org.dllearner.algorithms.ocel	New experimental refinement operator approach, which takes obtained information about concrete examples in an algorithm run stronger into account.
org.dllearner.algorithms.refinement	Refinement Operator Approach.
org.dllearner.core	Core structure of DL-Learner including the definition of component types and a component manager.
org.dllearner.core.fuzzydll
org.dllearner.core.owl	Classes/Interfaces for representing OWL constructs - see the OWL 2 Structural Specification for details.
org.dllearner.kb.sparql	Runnable scripts, each for a different task or experiment.
org.dllearner.learningproblems	Supported DL-Learner learning problems.
org.dllearner.learningproblems.fuzzydll
org.dllearner.parser	DL-Learner parsers.
org.dllearner.reasoning	Implements the connection to other reasoner or own reasoning/caching algorithms.
org.dllearner.reasoning.fuzzydll
org.dllearner.refinementoperators	Refinement operator implementations.
org.dllearner.refinementoperators.fuzzydll
org.dllearner.utilities	Utility classes.
org.dllearner.utilities.datastructures	Utility classesfor manipulating general data structures.
org.dllearner.utilities.examples	Utility classes related to finding/modifying examples of learning problems.
org.dllearner.utilities.owl	OWL utility classes (file manipulation, converting between different formats, orderings on OWL structures etc.).

Uses of Description in org.dllearner.algorithms

Methods in org.dllearner.algorithms that return Description
`Description`	`BruteForceLearner.getCurrentlyBestDescription()`
`Description`	`RandomGuesser.getCurrentlyBestDescription()`
`Description`	`SearchTreeNode.getExpression()` Gets the OWL 2 class expression at this search tree node.

Methods in org.dllearner.algorithms that return types with arguments of type Description
`List<Description>`	`DisjointClassesLearner.getCurrentlyBestDescriptions(int nrOfDescriptions)`
`List<Description>`	`SimpleSubclassLearner.getCurrentlyBestDescriptions(int nrOfDescriptions)`

Uses of Description in org.dllearner.algorithms.celoe

Methods in org.dllearner.algorithms.celoe that return Description
`Description`	`CELOE.getCurrentlyBestDescription()`
`Description`	`OENode.getDescription()`
`Description`	`OENode.getExpression()`

Methods in org.dllearner.algorithms.celoe that return types with arguments of type Description
`List<Description>`	`CELOE.getCurrentlyBestDescriptions()`

Constructors in org.dllearner.algorithms.celoe with parameters of type Description
`OENode(OENode parentNode, Description description, double accuracy)`

Uses of Description in org.dllearner.algorithms.el

Methods in org.dllearner.algorithms.el that return Description
`Description`	`ELLearningAlgorithmDisjunctive.getCurrentlyBestDescription()`
`Description`	`ELLearningAlgorithm.getCurrentlyBestDescription()`
`Description`	`ELDescriptionTree.transformToDescription()`
`Description`	`ELDescriptionNode.transformToDescription()` This method transform the tree to an EL description.

Methods in org.dllearner.algorithms.el that return types with arguments of type Description
`List<Description>`	`ELLearningAlgorithm.getCurrentlyBestDescriptions()`

Constructors in org.dllearner.algorithms.el with parameters of type Description
`ELDescriptionTree(AbstractReasonerComponent rs, Description description)` Constructs an EL description tree from an EL description.

Uses of Description in org.dllearner.algorithms.fuzzydll

Methods in org.dllearner.algorithms.fuzzydll that return Description
`Description`	`FuzzyCELOE.getCurrentlyBestDescription()`
`Description`	`FuzzyOENode.getDescription()`
`Description`	`FuzzyOENode.getExpression()`

Methods in org.dllearner.algorithms.fuzzydll that return types with arguments of type Description
`List<Description>`	`FuzzyCELOE.getCurrentlyBestDescriptions()`
`List<Description>`	`FuzzyCELOE.getCurrentlyBestDescriptions(int nrOfDescriptions)`

Constructors in org.dllearner.algorithms.fuzzydll with parameters of type Description
`FuzzyOENode(FuzzyOENode parentNode, Description description, double accuracy)`

Uses of Description in org.dllearner.algorithms.gp

Subclasses of Description in org.dllearner.algorithms.gp
`class`	`ADC` ADC stand for "automatically defined concept".

Methods in org.dllearner.algorithms.gp that return Description
`static Description`	`GPUtilities.createGrowRandomTree(AbstractLearningProblem learningProblem, AbstractReasonerComponent rs, int depth, boolean useADC)`
`Description`	`Program.getAdc()`
`Description`	`GP.getCurrentlyBestDescription()`
`Description`	`Program.getTree()` Returns the program tree corresponding to this program.

Methods in org.dllearner.algorithms.gp with parameters of type Description
`static boolean`	`GPUtilities.checkTree(Description node, boolean isRootNode)`
`static Program`	`GPUtilities.createProgram(AbstractLearningProblem learningProblem, Description mainTree)`

Constructors in org.dllearner.algorithms.gp with parameters of type Description
`Program(ScorePosNeg score, Description hypothesis)` Create a new program.
`Program(ScorePosNeg score, Description hypothesis, Description adc)`

Uses of Description in org.dllearner.algorithms.hybridgp

Fields in org.dllearner.algorithms.hybridgp with type parameters of type Description
`SortedMap<Description,ScorePosNeg>`	`Psi.evalCache`
`SortedMap<Description,Set<Description>>`	`Psi.pdCache`
`SortedMap<Description,Set<Description>>`	`Psi.pdCache`
`SortedMap<Description,Set<Description>>`	`Psi.puCache`
`SortedMap<Description,Set<Description>>`	`Psi.puCache`

Methods in org.dllearner.algorithms.hybridgp that return Description
`Description`	`Psi.applyPsi(Description concept, int coveredPositives, int coveredNegatives)`

Methods in org.dllearner.algorithms.hybridgp that return types with arguments of type Description
`SortedMap<Description,Set<Description>>`	`Psi.getPdCache()`
`SortedMap<Description,Set<Description>>`	`Psi.getPdCache()`
`SortedMap<Description,Set<Description>>`	`Psi.getPuCache()`
`SortedMap<Description,Set<Description>>`	`Psi.getPuCache()`

Methods in org.dllearner.algorithms.hybridgp with parameters of type Description
`Description`	`Psi.applyPsi(Description concept, int coveredPositives, int coveredNegatives)`

Uses of Description in org.dllearner.algorithms.isle

Methods in org.dllearner.algorithms.isle that return Description
`Description`	`ISLE.getCurrentlyBestDescription()`

Methods in org.dllearner.algorithms.isle that return types with arguments of type Description
`List<Description>`	`ISLE.getCurrentlyBestDescriptions()`

Uses of Description in org.dllearner.algorithms.ocel

Methods in org.dllearner.algorithms.ocel that return Description
`Description`	`ROLearner2.getBestSolution()`
`Description`	`ExampleBasedNode.getConcept()`
`Description`	`OCEL.getCurrentlyBestDescription()`
`Description`	`ExampleBasedNode.getExpression()`

Methods in org.dllearner.algorithms.ocel that return types with arguments of type Description
`SortedSet<Description>`	`ExampleBasedNode.getChildConcepts()`
`List<Description>`	`OCEL.getCurrentlyBestDescriptions()`
`List<Description>`	`ROLearner2.getCurrentlyBestDescriptions()`

Methods in org.dllearner.algorithms.ocel with parameters of type Description
`int`	`SubsumptionComparator.compare(Description concept1, Description concept2)`

Constructors in org.dllearner.algorithms.ocel with parameters of type Description
`ExampleBasedNode(OCELConfigurator configurator, Description concept)`
ROLearner2(OCELConfigurator configurator, AbstractLearningProblem learningProblem, AbstractReasonerComponent rs, RefinementOperator operator, ExampleBasedHeuristic heuristic, Description startDescription, double noise, boolean writeSearchTree, boolean replaceSearchTree, File searchTreeFile, boolean useTooWeakList, boolean useOverlyGeneralList, boolean useShortConceptConstruction, boolean usePropernessChecks, int maxPosOnlyExpansion, int maxExecutionTimeInSeconds, int minExecutionTimeInSeconds, int guaranteeXgoodDescriptions, int maxClassDescriptionTests, boolean forceRefinementLengthIncrease)

Constructors in org.dllearner.algorithms.ocel with parameters of type Description

ExampleBasedNode(OCELConfigurator configurator,
                                 Description concept)

ROLearner2(OCELConfigurator configurator,
                     AbstractLearningProblem learningProblem,
                     AbstractReasonerComponent rs,
                     RefinementOperator operator,
                     ExampleBasedHeuristic heuristic,
                     Description startDescription,
                     double noise,
                     boolean writeSearchTree,
                     boolean replaceSearchTree,
                     File searchTreeFile,
                     boolean useTooWeakList,
                     boolean useOverlyGeneralList,
                     boolean useShortConceptConstruction,
                     boolean usePropernessChecks,
                     int maxPosOnlyExpansion,
                     int maxExecutionTimeInSeconds,
                     int minExecutionTimeInSeconds,
                     int guaranteeXgoodDescriptions,
                     int maxClassDescriptionTests,
                     boolean forceRefinementLengthIncrease)

Uses of Description in org.dllearner.algorithms.refinement

Methods in org.dllearner.algorithms.refinement that return Description
`Description`	`Node.getConcept()`
`Description`	`ROLearner.getCurrentlyBestDescription()`

Methods in org.dllearner.algorithms.refinement that return types with arguments of type Description
`Set<Description>`	`Node.getChildConcepts()`
`List<Description>`	`ROLearner.getCurrentlyBestDescriptions(int nrOfSolutions)`

Methods in org.dllearner.algorithms.refinement with parameters of type Description
`ScorePosNeg`	`ROLearner.getSolutionScore(Description d)`

Constructors in org.dllearner.algorithms.refinement with parameters of type Description
`Node(Description concept)`

Uses of Description in org.dllearner.core

Methods in org.dllearner.core that return Description
`abstract Description`	`AbstractCELA.getCurrentlyBestDescription()`
`Description`	`EvaluatedDescription.getDescription()` Gets the description, which was evaluated.
`Description`	`SchemaReasoner.getDomain(DatatypeProperty datatypeProperty)` Returns the domain of this data property.
`Description`	`AbstractReasonerComponent.getDomain(DatatypeProperty datatypeProperty)`
`Description`	`ReasonerOld.getDomain(DatatypeProperty datatypeProperty)` Deprecated.
`Description`	`SchemaReasoner.getDomain(ObjectProperty objectProperty)` Returns the domain of this object property.
`Description`	`AbstractReasonerComponent.getDomain(ObjectProperty objectProperty)`
`Description`	`ReasonerOld.getDomain(ObjectProperty objectProperty)` Deprecated.
`Description`	`SchemaReasoner.getRange(ObjectProperty objectProperty)` Returns the range of this object property.
`Description`	`AbstractReasonerComponent.getRange(ObjectProperty objectProperty)`
`Description`	`ReasonerOld.getRange(ObjectProperty objectProperty)` Deprecated.

Methods in org.dllearner.core that return types with arguments of type Description
`Set<Description>`	`SchemaReasoner.getAssertedDefinitions(NamedClass namedClass)` Returns all asserted owl:equivalence class axioms for the given class.
`Set<Description>`	`AbstractReasonerComponent.getAssertedDefinitions(NamedClass namedClass)`
`List<Description>`	`AbstractCELA.getCurrentlyBestDescriptions()`
`List<Description>`	`AbstractCELA.getCurrentlyBestDescriptions(int nrOfDescriptions)`
`List<Description>`	`ClassExpressionLearningAlgorithm.getCurrentlyBestDescriptions(int nrOfDescriptions)`
`List<Description>`	`FuzzyClassExpressionLearningAlgorithm.getCurrentlyBestDescriptions(int nrOfDescriptions)`
`List<Description>`	`AbstractCELA.getCurrentlyBestDescriptions(int nrOfDescriptions, boolean filterNonMinimalDescriptions)`
`SortedSet<Description>`	`SchemaReasoner.getSubClasses(Description description)` Returns direct sub classes in the class hierarchy.
`SortedSet<Description>`	`AbstractReasonerComponent.getSubClasses(Description concept)`
`SortedSet<Description>`	`SchemaReasoner.getSuperClasses(Description description)` Returns direct super classes in the class hierarchy.
`SortedSet<Description>`	`AbstractReasonerComponent.getSuperClasses(Description concept)`
`Set<Description>`	`SchemaReasoner.isSuperClassOf(Set<Description> superClasses, Description subClasses)` Checks which of `superClasses` are super classes of `subClass`
`Set<Description>`	`AbstractReasonerComponent.isSuperClassOf(Set<Description> superConcepts, Description subConcept)`
`Set<Description>`	`ReasonerOld.subsumes(Description superConcept, Set<Description> subConcepts)` Deprecated.
`Set<Description>`	`ReasonerOld.subsumes(Set<Description> superConcepts, Description subConcept)` Deprecated.

Methods in org.dllearner.core with parameters of type Description
`abstract Score`	`AbstractLearningProblem.computeScore(Description description)` Computes the `Score` of a given class description with respect to this learning problem.
`SortedSetTuple<Individual>`	`IndividualReasoner.doubleRetrieval(Description description)` Performs a query for all instances of the given class description and its negation.
`SortedSetTuple<Individual>`	`AbstractReasonerComponent.doubleRetrieval(Description concept)`
`SortedSetTuple<Individual>`	`ReasonerOld.doubleRetrieval(Description concept)` Deprecated.
`SortedSetTuple<Individual>`	`ReasonerOld.doubleRetrieval(Description concept, Description adc)` Deprecated.
`abstract EvaluatedDescription`	`AbstractLearningProblem.evaluate(Description description)` Evaluates the description by computing the score and returning an evaluated description of the correct type (ClassLearningProblem returns EvaluatedDescriptionClass instead of generic EvaluatedDescription).
`abstract double`	`AbstractLearningProblem.getAccuracy(Description description)` This method returns a value, which indicates how accurate a class description solves a learning problem.
`abstract double`	`AbstractLearningProblem.getAccuracyOrTooWeak(Description description, double noise)` This method computes the accuracy as `AbstractLearningProblem.getAccuracy(Description)`, but returns -1 instead of the accuracy if 1.) the accuracy of the description is below the given threshold and 2.) the accuracy of all more special w.r.t. subsumption descriptions is below the given threshold.
`SortedSet<FuzzyIndividual>`	`AbstractReasonerComponent.getFuzzyIndividuals(Description concept)`
`SortedSet<Individual>`	`IndividualReasoner.getIndividuals(Description description)` Gets all instances of a given class description in the knowledge base.
`SortedSet<Individual>`	`AbstractReasonerComponent.getIndividuals(Description concept)`
`SortedSet<Description>`	`SchemaReasoner.getSubClasses(Description description)` Returns direct sub classes in the class hierarchy.
`SortedSet<Description>`	`AbstractReasonerComponent.getSubClasses(Description concept)`
`SortedSet<Description>`	`SchemaReasoner.getSuperClasses(Description description)` Returns direct super classes in the class hierarchy.
`SortedSet<Description>`	`AbstractReasonerComponent.getSuperClasses(Description concept)`
`boolean`	`IndividualReasoner.hasType(Description description, Individual individual)` Checks whether `individual` is instance of `description`.
`boolean`	`AbstractReasonerComponent.hasType(Description concept, Individual s)`
`SortedSet<Individual>`	`IndividualReasoner.hasType(Description description, Set<Individual> individuals)` Performs instance checks on a set of instances (reasoners might be more efficient than handling each check separately).
`SortedSet<Individual>`	`AbstractReasonerComponent.hasType(Description concept, Set<Individual> s)`
`double`	`AbstractReasonerComponent.hasTypeFuzzyMembership(Description description, FuzzyIndividual individual)` FUZZY EXTENSIONS
`boolean`	`ReasonerOld.instanceCheck(Description concept, Individual individual)` Deprecated.
`SortedSet<Individual>`	`ReasonerOld.instanceCheck(Description concept, Set<Individual> individuals)` Deprecated.
`boolean`	`SchemaReasoner.isEquivalentClass(Description class1, Description class2)` Checks whether `class1` is equivalent to `class2`.
`boolean`	`AbstractReasonerComponent.isEquivalentClass(Description class1, Description class2)`
`boolean`	`SchemaReasoner.isSuperClassOf(Description superClass, Description subClass)` Checks whether `superClass` is a super class of `subClass`.
`boolean`	`AbstractReasonerComponent.isSuperClassOf(Description superClass, Description subClass)`
`Set<Description>`	`SchemaReasoner.isSuperClassOf(Set<Description> superClasses, Description subClasses)` Checks which of `superClasses` are super classes of `subClass`
`Set<Description>`	`AbstractReasonerComponent.isSuperClassOf(Set<Description> superConcepts, Description subConcept)`
`SortedSet<Individual>`	`ReasonerOld.retrieval(Description concept)` Deprecated.
`void`	`EvaluatedDescription.setDescription(Description description)` Used for rewriting (simplification, beautification) of evaluated descriptions returned by the learning algorithm.
`boolean`	`ReasonerOld.subsumes(Description superConcept, Description subConcept)` Deprecated.
`Set<Description>`	`ReasonerOld.subsumes(Description superConcept, Set<Description> subConcepts)` Deprecated.
`Set<Description>`	`ReasonerOld.subsumes(Set<Description> superConcepts, Description subConcept)` Deprecated.

Method parameters in org.dllearner.core with type arguments of type Description
`Set<Description>`	`SchemaReasoner.isSuperClassOf(Set<Description> superClasses, Description subClasses)` Checks which of `superClasses` are super classes of `subClass`
`Set<Description>`	`AbstractReasonerComponent.isSuperClassOf(Set<Description> superConcepts, Description subConcept)`
`Set<Description>`	`ReasonerOld.subsumes(Description superConcept, Set<Description> subConcepts)` Deprecated.
`Set<Description>`	`ReasonerOld.subsumes(Set<Description> superConcepts, Description subConcept)` Deprecated.

Constructors in org.dllearner.core with parameters of type Description
`EvaluatedDescription(Description description, Score score)` Constructs an evaluated description using its score.

Uses of Description in org.dllearner.core.fuzzydll

Methods in org.dllearner.core.fuzzydll with parameters of type Description
`SortedSet<FuzzyIndividual>`	`FuzzyIndividualReasoner.getFuzzyIndividuals(Description concept)`
`double`	`FuzzyIndividualReasoner.hasTypeFuzzyMembership(Description description, FuzzyIndividual individual)` Checks the fuzzy membership degree of `individual` over `description`.

Uses of Description in org.dllearner.core.owl

Subclasses of Description in org.dllearner.core.owl
`class`	`BooleanValueRestriction` Convenience class for boolean value restrictions.
`class`	`CardinalityRestriction`
`class`	`DatatypeCardinalityRestriction`
`class`	`DatatypeExactCardinalityRestriction`
`class`	`DatatypeMaxCardinalityRestriction`
`class`	`DatatypeMinCardinalityRestriction`
`class`	`DatatypeQuantorRestriction` Represents datatype quantor restrictions.
`class`	`DatatypeSomeRestriction` This class represents restrictions on datatypes, such as Man AND EXISTS hasAge >= 18.
`class`	`DatatypeValueRestriction` Examples for datatype value restrictions: Male AND hasAge HASVALUE 18 Male AND hasDriverLicense HASVALUE true
`class`	`Intersection`
`class`	`NamedClass` Represents an atomic concept in a knowledge base / ontology, e.g.
`class`	`Negation`
`class`	`Nothing` Implementation of owl:Nothing/BOTTOM.
`class`	`ObjectAllRestriction` All quantified restriction on objects, e.g.
`class`	`ObjectCardinalityRestriction`
`class`	`ObjectExactCardinalityRestriction`
`class`	`ObjectMaxCardinalityRestriction`
`class`	`ObjectMinCardinalityRestriction`
`class`	`ObjectOneOf`
`class`	`ObjectQuantorRestriction`
`class`	`ObjectSomeRestriction` Existantial restriction on objects, e.g.
`class`	`ObjectValueRestriction` Restricts the value of an object property to a single individual (corresponds to owl:hasValue)
`class`	`QuantorRestriction`
`class`	`Restriction` A restriction always acts along a property expression.
`class`	`StringValueRestriction` String value restriction, e.g.
`class`	`Thing` Implementation of owl:thing/TOP.
`class`	`Union`
`class`	`ValueRestriction`

Methods in org.dllearner.core.owl that return Description
`Description`	`Description.clone()` Returns a clone of this description.
`Description`	`Description.getChild(int i)`
`Description`	`ClassAssertionAxiom.getConcept()`
`Description`	`EquivalentClassesAxiom.getConcept1()`
`Description`	`EquivalentClassesAxiom.getConcept2()`
`Description`	`ContextDescription.getDescription()`
`Description`	`PropertyDomainAxiom.getDomain()`
`Description`	`ContextDescription.getParent()`
`Description`	`Description.getParent()`
`Description`	`ObjectPropertyRangeAxiom.getRange()`
`Description`	`SubClassAxiom.getSubConcept()`
`Description`	`Description.getSubtree(int i)` Selects a sub tree.
`Description`	`SubClassAxiom.getSuperConcept()`

Methods in org.dllearner.core.owl that return types with arguments of type Description
`List<Description>`	`Description.getChildren()`
`Set<Description>`	`DisjointClassesAxiom.getDescriptions()`
`SortedSet<Description>`	`ClassHierarchy.getSiblingClasses(Description description)` Computes the siblings of the specified descriptions.
`SortedSet<Description>`	`ClassHierarchy.getSubClasses(Description concept)`
`SortedSet<Description>`	`ClassHierarchy.getSuperClasses(Description concept)`

Methods in org.dllearner.core.owl with parameters of type Description
`void`	`Description.addChild(Description child)` Adds a description as child of this one.
`void`	`Description.addChild(int index, Description child)` Adds a child description at the specified index.
`Set<String>`	`KB.findAllRoleNames(Description concept)`
`SortedSet<Description>`	`ClassHierarchy.getSiblingClasses(Description description)` Computes the siblings of the specified descriptions.
`SortedSet<Description>`	`ClassHierarchy.getSubClasses(Description concept)`
`SortedSet<Description>`	`ClassHierarchy.getSuperClasses(Description concept)`
`void`	`Description.removeChild(Description child)` Remove the specified child description (its parent link is set to null).
`void`	`Description.replaceChild(int index, Description newChild)`
`void`	`Description.setParent(Description parent)`

Constructors in org.dllearner.core.owl with parameters of type Description
`ClassAssertionAxiom(Description concept, Individual individual)`
`ContextDescription(Description description, Description parent)`
`DatatypePropertyDomainAxiom(DatatypeProperty property, Description domain)`
`EquivalentClassesAxiom(Description concept1, Description concept2)`
`Intersection(Description... children)`
`Negation(Description c)`
`ObjectAllRestriction(ObjectPropertyExpression role, Description c)`
`ObjectCardinalityRestriction(int number, ObjectPropertyExpression role, Description c)`
`ObjectExactCardinalityRestriction(int number, ObjectPropertyExpression role, Description c)`
`ObjectMaxCardinalityRestriction(int number, ObjectPropertyExpression role, Description c)`
`ObjectMinCardinalityRestriction(int number, ObjectPropertyExpression role, Description c)`
`ObjectPropertyDomainAxiom(ObjectProperty property, Description domain)`
`ObjectPropertyRangeAxiom(ObjectProperty property, Description range)`
`ObjectQuantorRestriction(ObjectPropertyExpression role, Description c)`
`ObjectSomeRestriction(ObjectPropertyExpression role, Description c)`
`PropertyDomainAxiom(Property property, Description domain)`
`SubClassAxiom(Description subConcept, Description superConcept)`
`Union(Description... children)`

Constructor parameters in org.dllearner.core.owl with type arguments of type Description
`ClassHierarchy(TreeMap<Description,SortedSet<Description>> subsumptionHierarchyUp, TreeMap<Description,SortedSet<Description>> subsumptionHierarchyDown)` The arguments specify the superclasses and subclasses of each class.
`ClassHierarchy(TreeMap<Description,SortedSet<Description>> subsumptionHierarchyUp, TreeMap<Description,SortedSet<Description>> subsumptionHierarchyDown)` The arguments specify the superclasses and subclasses of each class.
`ClassHierarchy(TreeMap<Description,SortedSet<Description>> subsumptionHierarchyUp, TreeMap<Description,SortedSet<Description>> subsumptionHierarchyDown)` The arguments specify the superclasses and subclasses of each class.
`ClassHierarchy(TreeMap<Description,SortedSet<Description>> subsumptionHierarchyUp, TreeMap<Description,SortedSet<Description>> subsumptionHierarchyDown)` The arguments specify the superclasses and subclasses of each class.
`DisjointClassesAxiom(Set<Description> descriptions)`
`Intersection(List<Description> children)`
`Union(List<Description> children)`

Uses of Description in org.dllearner.kb.sparql

Methods in org.dllearner.kb.sparql with parameters of type Description
`static String`	`NaturalLanguageDescriptionConvertVisitor.getNaturalLanguageDescription(Description description, AbstractReasonerComponent service)`
`String`	`SparqlQueryDescriptionConvertVisitor.getSparqlQuery(Description description)` takes a description and transforms it into SPARQL
`static String`	`SparqlQueryDescriptionConvertVisitor.getSparqlQuery(Description description, int limit, boolean labels, boolean distinct)`

Uses of Description in org.dllearner.learningproblems

Methods in org.dllearner.learningproblems with parameters of type Description
`ScorePosNeg`	`PosNegLPStrict.computeScore(Description concept)`
`ScorePosOnly`	`PosOnlyLP.computeScore(Description description)`
`ClassScore`	`ClassLearningProblem.computeScore(Description description)`
`ScorePosNeg`	`PosNegLPStandard.computeScore(Description concept)` Computes score of a given concept using the reasoner.
`int`	`PosNegLPStrict.coveredNegativeExamplesOrTooWeak(Description concept)`
`abstract int`	`PosNegLP.coveredNegativeExamplesOrTooWeak(Description concept)`
`int`	`PosNegLPStandard.coveredNegativeExamplesOrTooWeak(Description concept)` This method computes (using the reasoner) whether a concept is too weak.
`EvaluatedDescription`	`PosNegLPStrict.evaluate(Description description)`
`EvaluatedDescriptionPosOnly`	`PosOnlyLP.evaluate(Description description)`
`EvaluatedDescriptionClass`	`ClassLearningProblem.evaluate(Description description)`
`EvaluatedDescription`	`PosNegLPStandard.evaluate(Description description)`
`boolean`	`ClassLearningProblem.followsFromKB(Description description)`
`double`	`PosNegLPStrict.getAccuracy(Description description)`
`double`	`PosOnlyLP.getAccuracy(Description description)`
`double`	`ClassLearningProblem.getAccuracy(Description description)`
`double`	`PosNegLPStandard.getAccuracy(Description description)`
`double`	`PosNegLPStrict.getAccuracyOrTooWeak(Description description, double minAccuracy)`
`double`	`PosOnlyLP.getAccuracyOrTooWeak(Description description, double noise)`
`double`	`ClassLearningProblem.getAccuracyOrTooWeak(Description description, double noise)`
`double`	`PosNegLPStandard.getAccuracyOrTooWeak(Description description, double noise)`
`double`	`ClassLearningProblem.getAccuracyOrTooWeakApprox(Description description, double noise)`
`double`	`PosNegLPStandard.getAccuracyOrTooWeakApprox(Description description, double noise)`
`double`	`ClassLearningProblem.getAccuracyOrTooWeakExact(Description description, double noise)`
`double`	`PosNegLPStandard.getAccuracyOrTooWeakExact(Description description, double noise)`
`double`	`PosNegLPStandard.getFMeasureOrTooWeakApprox(Description description, double noise)` Deprecated.
`double`	`PosNegLPStandard.getFMeasureOrTooWeakExact(Description description, double noise)`
`double`	`ClassLearningProblem.getPrecision(Description description)`
`double`	`PosNegLPStandard.getPredAccuracyOrTooWeakExact(Description description, double noise)`
`double`	`ClassLearningProblem.getRecall(Description description)`
`SortedSetTuple<Individual>`	`EvaluationCache.infer(Description concept)` Determines which examples are instances of a concept.
`boolean`	`ClassLearningProblem.isConsistent(Description description)`
`void`	`EvaluationCache.put(Description concept, SortedSet<Individual> individuals)`

Constructors in org.dllearner.learningproblems with parameters of type Description
`EvaluatedDescriptionClass(Description description, ClassScore score)` Constructs an evaluated description for learning classes in ontologies.
`EvaluatedDescriptionPosNeg(Description description, ScorePosNeg score)` Constructs an evaluated description using its score.
`EvaluatedDescriptionPosNeg(Description description, Set<Individual> posAsPos, Set<Individual> posAsNeg, Set<Individual> negAsPos, Set<Individual> negAsNeg)` Constructs an evaluated description using example coverage.
`EvaluatedDescriptionPosOnly(Description description, ScorePosOnly score)`

Uses of Description in org.dllearner.learningproblems.fuzzydll

Methods in org.dllearner.learningproblems.fuzzydll with parameters of type Description
`ScorePosNeg`	`FuzzyPosNegLPStandard.computeScore(Description concept)` Computes score of a given concept using the reasoner.
`int`	`FuzzyPosNegLPStandard.coveredNegativeExamplesOrTooWeak(Description concept)` This method computes (using the reasoner) whether a concept is too weak.
`abstract int`	`FuzzyPosNegLP.coveredNegativeExamplesOrTooWeak(Description concept)`
`EvaluatedDescription`	`FuzzyPosNegLPStandard.evaluate(Description description)`
`double`	`FuzzyPosNegLPStandard.getAccuracy(Description description)`
`double`	`FuzzyPosNegLPStandard.getAccuracyOrTooWeak(Description description, double noise)`
`double`	`FuzzyPosNegLPStandard.getAccuracyOrTooWeakApprox(Description description, double noise)`
`double`	`FuzzyPosNegLPStandard.getAccuracyOrTooWeakExact(Description description, double noise)`
`double`	`FuzzyPosNegLPStandard.getFMeasureOrTooWeakApprox(Description description, double noise)` Deprecated.
`double`	`FuzzyPosNegLPStandard.getFMeasureOrTooWeakExact(Description description, double noise)`
`double`	`FuzzyPosNegLPStandard.getPredAccuracyOrTooWeakExact(Description description, double noise)`

Uses of Description in org.dllearner.parser

Methods in org.dllearner.parser that return Description
`Description`	`KBParser.Concept()`
`static Description`	`KBParser.parseConcept(String string)`
`static Description`	`KBParser.parseConcept(String string, String namespace)`

Uses of Description in org.dllearner.reasoning

Methods in org.dllearner.reasoning that return Description
`Description`	`SPARQLReasoner.getDomain(DatatypeProperty datatypeProperty)`
`Description`	`SPARQLReasoner.getDomain(ObjectProperty objectProperty)`
`Description`	`ProtegeReasoner.getDomainImpl(DatatypeProperty datatypeProperty)`
`Description`	`OWLAPIReasoner.getDomainImpl(DatatypeProperty datatypeProperty)`
`Description`	`PelletReasoner.getDomainImpl(DatatypeProperty datatypeProperty)`
`Description`	`FastInstanceChecker.getDomainImpl(DatatypeProperty datatypeProperty)`
`Description`	`ProtegeReasoner.getDomainImpl(ObjectProperty objectProperty)`
`Description`	`OWLAPIReasoner.getDomainImpl(ObjectProperty objectProperty)`
`Description`	`PelletReasoner.getDomainImpl(ObjectProperty objectProperty)`
`Description`	`FastInstanceChecker.getDomainImpl(ObjectProperty objectProperty)`
`Description`	`SPARQLReasoner.getRange(ObjectProperty objectProperty)`
`Description`	`ProtegeReasoner.getRangeImpl(ObjectProperty objectProperty)`
`Description`	`OWLAPIReasoner.getRangeImpl(ObjectProperty objectProperty)`
`Description`	`PelletReasoner.getRangeImpl(ObjectProperty objectProperty)`
`Description`	`FastInstanceChecker.getRangeImpl(ObjectProperty objectProperty)`

Methods in org.dllearner.reasoning that return types with arguments of type Description
`Set<Description>`	`SPARQLReasoner.getAssertedDefinitions(NamedClass namedClass)`
`Set<Description>`	`ProtegeReasoner.getComplementClasses(Description desc)`
`Set<Description>`	`PelletReasoner.getComplementClasses(Description desc)`
`SortedSet<Description>`	`SPARQLReasoner.getSubClasses(Description description)`
`SortedSet<Description>`	`SPARQLReasoner.getSuperClasses(Description description)`
`SortedSet<Description>`	`SPARQLReasoner.getSuperClasses(Description description, boolean direct)`
`Set<Description>`	`SPARQLReasoner.isSuperClassOf(Set<Description> superClasses, Description subClasses)`
`Set<Description>`	`DIGReasoner.isSuperClassOfImpl(Set<Description> superConcepts, Description subConcept)`

Methods in org.dllearner.reasoning with parameters of type Description
`SortedSetTuple<String>`	`FastRetrieval.calculateSets(Description concept)`
`SortedSetTuple<String>`	`FastRetrieval.calculateSetsADC(Description concept, SortedSetTuple<String> adcSet)`
`SortedSetTuple<Individual>`	`SPARQLReasoner.doubleRetrieval(Description description)`
`SortedSetTuple<Individual>`	`FastRetrievalReasoner.doubleRetrievalImpl(Description concept)`
`Set<Description>`	`ProtegeReasoner.getComplementClasses(Description desc)`
`Set<Description>`	`PelletReasoner.getComplementClasses(Description desc)`
`static StringBuilder`	`DIGConverter.getDIGString(Description concept)`
`SortedSet<Individual>`	`SPARQLReasoner.getIndividuals(Description description)`
`SortedSet<Individual>`	`SPARQLReasoner.getIndividuals(Description description, int limit)`
`SortedSet<Individual>`	`ProtegeReasoner.getIndividualsImpl(Description concept)`
`SortedSet<Individual>`	`OWLAPIReasoner.getIndividualsImpl(Description concept)`
`SortedSet<Individual>`	`PelletReasoner.getIndividualsImpl(Description concept)`
`SortedSet<Individual>`	`DIGReasoner.getIndividualsImpl(Description concept)`
`SortedSet<Individual>`	`FastRetrievalReasoner.getIndividualsImpl(Description concept)`
`SortedSet<Individual>`	`FastInstanceChecker.getIndividualsImpl(Description concept)`
`SortedSet<Individual>`	`ProtegeReasoner.getIndividualsImplFast(Description description)`
`SortedSet<Individual>`	`PelletReasoner.getIndividualsImplFast(Description description)`
`SortedSet<Individual>`	`FastInstanceChecker.getIndividualsImplFast(Description description)`
`SortedSet<Individual>`	`ProtegeReasoner.getIndividualsImplStandard(Description concept)`
`SortedSet<Individual>`	`PelletReasoner.getIndividualsImplStandard(Description concept)`
`SortedSet<Individual>`	`FastInstanceChecker.getIndividualsImplStandard(Description concept)`
`SortedSet<Description>`	`SPARQLReasoner.getSubClasses(Description description)`
`SortedSet<Description>`	`SPARQLReasoner.getSuperClasses(Description description)`
`SortedSet<Description>`	`SPARQLReasoner.getSuperClasses(Description description, boolean direct)`
`boolean`	`SPARQLReasoner.hasType(Description description, Individual individual)`
`SortedSet<Individual>`	`SPARQLReasoner.hasType(Description description, Set<Individual> individuals)`
`boolean`	`ProtegeReasoner.hasTypeImpl(Description description, Individual individual)`
`boolean`	`OWLAPIReasoner.hasTypeImpl(Description concept, Individual individual)`
`boolean`	`PelletReasoner.hasTypeImpl(Description description, Individual individual)`
`boolean`	`DIGReasoner.hasTypeImpl(Description concept, Individual individual)`
`boolean`	`FastRetrievalReasoner.hasTypeImpl(Description concept, Individual individual)`
`boolean`	`FastInstanceChecker.hasTypeImpl(Description description, Individual individual)`
`SortedSet<Individual>`	`DIGReasoner.hasTypeImpl(Description concept, Set<Individual> individuals)`
`boolean`	`SPARQLReasoner.isEquivalentClass(Description class1, Description class2)`
`boolean`	`SPARQLReasoner.isSuperClassOf(Description superClass, Description subClass)`
`Set<Description>`	`SPARQLReasoner.isSuperClassOf(Set<Description> superClasses, Description subClasses)`
`boolean`	`ProtegeReasoner.isSuperClassOfImpl(Description superConcept, Description subConcept)`
`boolean`	`OWLAPIReasoner.isSuperClassOfImpl(Description superConcept, Description subConcept)`
`boolean`	`PelletReasoner.isSuperClassOfImpl(Description superConcept, Description subConcept)`
`boolean`	`DIGReasoner.isSuperClassOfImpl(Description superConcept, Description subConcept)`
`boolean`	`FastRetrievalReasoner.isSuperClassOfImpl(Description superConcept, Description subConcept)`
`boolean`	`FastInstanceChecker.isSuperClassOfImpl(Description superConcept, Description subConcept)`
`Set<Description>`	`DIGReasoner.isSuperClassOfImpl(Set<Description> superConcepts, Description subConcept)`

Method parameters in org.dllearner.reasoning with type arguments of type Description
`Set<Description>`	`SPARQLReasoner.isSuperClassOf(Set<Description> superClasses, Description subClasses)`
`Set<Description>`	`DIGReasoner.isSuperClassOfImpl(Set<Description> superConcepts, Description subConcept)`

Uses of Description in org.dllearner.reasoning.fuzzydll

Methods in org.dllearner.reasoning.fuzzydll that return Description
`Description`	`FuzzyOWLAPIReasoner.getDomainImpl(DatatypeProperty datatypeProperty)`
`Description`	`FuzzyOWLAPIReasoner.getDomainImpl(ObjectProperty objectProperty)`
`Description`	`FuzzyOWLAPIReasoner.getRangeImpl(ObjectProperty objectProperty)`

Methods in org.dllearner.reasoning.fuzzydll with parameters of type Description
`SortedSet<FuzzyIndividual>`	`FuzzyOWLAPIReasoner.getFuzzyIndividualsImpl(Description concept)`
`SortedSet<Individual>`	`FuzzyOWLAPIReasoner.getIndividualsImpl(Description concept)`
`double`	`FuzzyOWLAPIReasoner.hasTypeFuzzyMembershipImpl(Description description, FuzzyIndividual individual)` FUZZY EXTENSIONS
`boolean`	`FuzzyOWLAPIReasoner.hasTypeImpl(Description concept, Individual individual)`
`boolean`	`FuzzyOWLAPIReasoner.isSuperClassOfImpl(Description superConcept, Description subConcept)`

Uses of Description in org.dllearner.refinementoperators

Methods in org.dllearner.refinementoperators that return types with arguments of type Description
`SortedSet<Description>`	`RhoDRDown.getClassCandidates(NamedClass index)`
`SortedSet<Description>`	`RhoDRDown.getNegClassCandidates(NamedClass index)`
`Set<Description>`	`PsiUp.refine(Description concept)`
`Set<Description>`	`OperatorInverter.refine(Description description)`
`Set<Description>`	`ELDown.refine(Description concept)`
`abstract Set<Description>`	`RefinementOperatorAdapter.refine(Description description)`
`Set<Description>`	`PsiDown.refine(Description concept)`
`Set<Description>`	`ELDown2.refine(Description concept)`
`Set<Description>`	`RhoDown.refine(Description concept)`
`Set<Description>`	`RhoDRDown.refine(Description concept)`
`Set<Description>`	`RefinementOperator.refine(Description description)` Standard refinement operation.
`Set<Description>`	`OperatorInverter.refine(Description description, int maxLength)`
`Set<Description>`	`RefinementOperatorAdapter.refine(Description description, int maxLength)`
`Set<Description>`	`RhoDRDown.refine(Description description, int maxLength)`
`Set<Description>`	`RefinementOperator.refine(Description description, int maxLength)` Optional refinement operation, where the learning algorithm can specify an additional bound on the length of descriptions.
`Set<Description>`	`PsiUp.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`OperatorInverter.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RefinementOperatorAdapter.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`PsiDown.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`SortedSet<Description>`	`RhoDown.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RefinementOperator.refine(Description description, int maxLength, List<Description> knownRefinements)` Optional refinement operation, where the learning algorithm can specify an additional bound on the length of descriptions and a list of known refinements, which do not need to be returned.
`Set<Description>`	`RhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements, Description currDomain)`

Methods in org.dllearner.refinementoperators with parameters of type Description
`SortedSet<ObjectProperty>`	`Utility.computeApplicableObjectProperties(Description index)` Compute the set of applicable object properties for a given description.
`static boolean`	`MathOperations.containsDoubleObjectSomeRestriction(Description d)` Returns true if the same property is used twice in an object some restriction, e.g.
`Set<NamedClass>`	`Utility.getClassCandidates(Description index, Set<NamedClass> existingClasses)`
`boolean`	`Utility.isDisjoint(Description d1, Description d2)`
`Set<Description>`	`PsiUp.refine(Description concept)`
`Set<Description>`	`OperatorInverter.refine(Description description)`
`Set<Description>`	`ELDown.refine(Description concept)`
`abstract Set<Description>`	`RefinementOperatorAdapter.refine(Description description)`
`Set<Description>`	`PsiDown.refine(Description concept)`
`Set<Description>`	`ELDown2.refine(Description concept)`
`Set<Description>`	`RhoDown.refine(Description concept)`
`Set<Description>`	`RhoDRDown.refine(Description concept)`
`Set<Description>`	`RefinementOperator.refine(Description description)` Standard refinement operation.
`Set<Description>`	`OperatorInverter.refine(Description description, int maxLength)`
`Set<Description>`	`RefinementOperatorAdapter.refine(Description description, int maxLength)`
`Set<Description>`	`RhoDRDown.refine(Description description, int maxLength)`
`Set<Description>`	`RefinementOperator.refine(Description description, int maxLength)` Optional refinement operation, where the learning algorithm can specify an additional bound on the length of descriptions.
`Set<Description>`	`PsiUp.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`OperatorInverter.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RefinementOperatorAdapter.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`PsiDown.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`SortedSet<Description>`	`RhoDown.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RefinementOperator.refine(Description description, int maxLength, List<Description> knownRefinements)` Optional refinement operation, where the learning algorithm can specify an additional bound on the length of descriptions and a list of known refinements, which do not need to be returned.
`Set<Description>`	`RhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements, Description currDomain)`

Method parameters in org.dllearner.refinementoperators with type arguments of type Description
`static SortedSet<Union>`	`MathOperations.incCrossProduct(Set<Union> baseSet, Set<Description> newSet)` Implements a cross product in the sense that each union description in the base set is extended by each description in the new set.
`Set<Description>`	`PsiUp.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`OperatorInverter.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RefinementOperatorAdapter.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`PsiDown.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`SortedSet<Description>`	`RhoDown.refine(Description concept, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`RefinementOperator.refine(Description description, int maxLength, List<Description> knownRefinements)` Optional refinement operation, where the learning algorithm can specify an additional bound on the length of descriptions and a list of known refinements, which do not need to be returned.
`Set<Description>`	`RhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements, Description currDomain)`

Constructors in org.dllearner.refinementoperators with parameters of type Description
`RhoDRDown(AbstractReasonerComponent reasoner, ClassHierarchy subHierarchy, Description startClass, RefinementOperatorConfigurator configurator)`

Constructor parameters in org.dllearner.refinementoperators with type arguments of type Description
`Utility(AbstractReasonerComponent rs, Map<ObjectProperty,Description> opDomains, boolean instanceBasedDisjoints)`

Uses of Description in org.dllearner.refinementoperators.fuzzydll

Methods in org.dllearner.refinementoperators.fuzzydll that return types with arguments of type Description
`SortedSet<Description>`	`FuzzyRhoDRDown.getClassCandidates(NamedClass index)`
`SortedSet<Description>`	`FuzzyRhoDRDown.getNegClassCandidates(NamedClass index)`
`Set<Description>`	`FuzzyRhoDRDown.refine(Description concept)`
`Set<Description>`	`FuzzyRhoDRDown.refine(Description description, int maxLength)`
`Set<Description>`	`FuzzyRhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`FuzzyRhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements, Description currDomain)`

Methods in org.dllearner.refinementoperators.fuzzydll with parameters of type Description
`Set<Description>`	`FuzzyRhoDRDown.refine(Description concept)`
`Set<Description>`	`FuzzyRhoDRDown.refine(Description description, int maxLength)`
`Set<Description>`	`FuzzyRhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`FuzzyRhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements, Description currDomain)`

Method parameters in org.dllearner.refinementoperators.fuzzydll with type arguments of type Description
`Set<Description>`	`FuzzyRhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements)`
`Set<Description>`	`FuzzyRhoDRDown.refine(Description description, int maxLength, List<Description> knownRefinements, Description currDomain)`

Constructors in org.dllearner.refinementoperators.fuzzydll with parameters of type Description
`FuzzyRhoDRDown(AbstractReasonerComponent reasoner, ClassHierarchy subHierarchy, Description startClass, RefinementOperatorConfigurator configurator)`

Uses of Description in org.dllearner.utilities

Methods in org.dllearner.utilities with parameters of type Description
`static List<NamedClass>`	`Helper.getAtomicConcepts(Description concept)`
`static List<ObjectProperty>`	`Helper.getAtomicRoles(Description concept)`

Uses of Description in org.dllearner.utilities.datastructures

Methods in org.dllearner.utilities.datastructures that return Description
`Description`	`DescriptionSubsumptionTree.Node.getDesc()`

Uses of Description in org.dllearner.utilities.examples

Methods in org.dllearner.utilities.examples with parameters of type Description
`void`	`AutomaticPositiveExampleFinderOWL.makePositiveExamplesFromConcept(Description concept)`

Uses of Description in org.dllearner.utilities.owl

Methods in org.dllearner.utilities.owl that return Description
`static Description`	`ConceptTransformation.applyEquivalenceRules(Description concept)`
`static Description`	`OWLAPIConverter.convertClass(org.semanticweb.owlapi.model.OWLClass owlClass)`
`static Description`	`ManchesterOWLSyntaxParser.getDescription(String manchesterSyntaxDescription)`
`Description`	`DLLearnerDescriptionConvertVisitor.getDLLearnerDescription()`
`static Description`	`DLLearnerDescriptionConvertVisitor.getDLLearnerDescription(org.semanticweb.owlapi.model.OWLClassExpression description)`
`static Description`	`ConceptTransformation.getShortConcept(Description concept, ConceptComparator conceptComparator)` Tries to shorten a concept, e.g. male AND male is shortened to male.
`static Description`	`ConceptTransformation.getShortConceptNonRecursive(Description concept, ConceptComparator conceptComparator)`
`Description`	`DescriptionMinimizer.minimize(Description description)` Same as `DescriptionMinimizer.minimizeClone(Description)`, but with no guarantee that the input description remains unmodified.
`Description`	`DescriptionMinimizer.minimizeClone(Description description)` Method which minimzes the input description.
`Description`	`PropertyContext.toExistentialContext()` Transforms context [r,s] to \exists r.
`static Description`	`ConceptTransformation.transformToNegationNormalForm(Description concept)`

Methods in org.dllearner.utilities.owl that return types with arguments of type Description
`SortedSet<Description>`	`DescriptionSet.getSet()`
`List<Description>`	`EvaluatedDescriptionSet.toDescriptionList()`

Methods in org.dllearner.utilities.owl with parameters of type Description
`void`	`DescriptionSet.add(Description ed)`
`void`	`EvaluatedDescriptionSet.add(Description description, double accuracy, AbstractLearningProblem problem)`
`static Description`	`ConceptTransformation.applyEquivalenceRules(Description concept)`
`static void`	`ConceptTransformation.cleanConcept(Description concept)`
`static void`	`ConceptTransformation.cleanConceptNonRecursive(Description concept)`
`int`	`ConceptComparator.compare(Description concept1, Description concept2)`
`static SortedSet<PropertyContext>`	`ConceptTransformation.getForallContexts(Description description)` Gets the "contexts" of all \forall occurrences in a description.
`static int`	`ConceptTransformation.getForallOccurences(Description description)` Counts occurrences of \forall in description.
`static org.semanticweb.owlapi.model.OWLClassExpression`	`OWLAPIConverter.getOWLAPIDescription(Description description)` Converts a DL-Learner description into an OWL API description.
`static org.semanticweb.owlapi.model.OWLClassExpression`	`OWLAPIDescriptionConvertVisitor.getOWLClassExpression(Description description)` Converts a DL-Learner description into an OWL API decription.
`static Description`	`ConceptTransformation.getShortConcept(Description concept, ConceptComparator conceptComparator)` Tries to shorten a concept, e.g. male AND male is shortened to male.
`static Description`	`ConceptTransformation.getShortConceptNonRecursive(Description concept, ConceptComparator conceptComparator)`
`static boolean`	`ConceptTransformation.isDescriptionMinimal(Description description)` Method to determine, whether a class description is minimal, e.g.
`static boolean`	`ConceptTransformation.isSubdescription(Description description, Description subDescription)` Tests whether a description is a subdescription in the sense that when parts of `description` can be removed to yield `subdescription`.
`Description`	`DescriptionMinimizer.minimize(Description description)` Same as `DescriptionMinimizer.minimizeClone(Description)`, but with no guarantee that the input description remains unmodified.
`Description`	`DescriptionMinimizer.minimizeClone(Description description)` Method which minimzes the input description.
`static void`	`ConceptTransformation.replaceRange(Description description, AbstractReasonerComponent rs)`
`static Description`	`ConceptTransformation.transformToNegationNormalForm(Description concept)`
`static void`	`ConceptTransformation.transformToOrderedForm(Description concept, Comparator<Description> conceptComparator)`
`static void`	`ConceptTransformation.transformToOrderedNegationNormalFormNonRecursive(Description concept, Comparator<Description> conceptComparator)`

Method parameters in org.dllearner.utilities.owl with type arguments of type Description
`void`	`DescriptionSet.addAll(Collection<Description> eds)`
`static void`	`ConceptTransformation.transformToOrderedForm(Description concept, Comparator<Description> conceptComparator)`
`static void`	`ConceptTransformation.transformToOrderedNegationNormalFormNonRecursive(Description concept, Comparator<Description> conceptComparator)`

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Uses of Classorg.dllearner.core.owl.Description

Uses of Class
org.dllearner.core.owl.Description