DL-Learner Components
Filter components by implemented interfaces:
- show all
- KnowledgeSource
- ReasonerComponent
- LearningProblem
- LearningAlgorithm
- RefinementOperator
- other
Click on a component to get an overview on its configuration options.
Brute Force Learner
short name: bruteForce
version: 0.8
implements: LearningAlgorithm, ClassExpressionLearningAlgorithm
This component does not have configuration options.
CELOE
short name: celoe
version: 1.0
implements: LearningAlgorithm, ClassExpressionLearningAlgorithm
description: CELOE is an adapted and extended version of the OCEL algorithm applied for the ontology engineering use case. See http://jens-lehmann.org/files/2011/celoe.pdf for reference.
option name | description | type | default value | required? |
---|---|---|---|---|
maxExecutionTimeInSecondsAfterImprovement | maximum execution of the algorithm in seconds | int | 0 | false |
startClass | You can specify a start class for the algorithm. To do this, you have to use Manchester OWL syntax without using prefixes. | Description | owl:Thing | false |
noisePercentage | the (approximated) percentage of noise within the examples | double | 0.0 | false |
terminateOnNoiseReached | specifies whether to terminate when noise criterion is met | boolean | false | false |
writeSearchTree | specifies whether to write a search tree | boolean | false | false |
filterDescriptionsFollowingFromKB | If true, then the results will not contain suggestions, which already follow logically from the knowledge base. Be careful, since this requires a potentially expensive consistency check for candidate solutions. | boolean | false | false |
maxDepth | maximum depth of description | double | 7 | false |
searchTreeFile | file to use for the search tree | String | log/searchTree.txt | false |
maxExecutionTimeInSeconds | maximum execution of the algorithm in seconds | int | 10 | false |
useMinimizer | Specifies whether returned expressions should be minimised by removing those parts, which are not needed. (Basically the minimiser tries to find the shortest expression which is equivalent to the learned expression). Turning this feature off may improve performance. | boolean | true | false |
maxClassExpressionTestsAfterImprovement | The maximum number of candidate hypothesis the algorithm is allowed after an improvement in accuracy (0 = no limit). The algorithm will stop afterwards. (The real number of tests can be slightly higher, because this criterion usually won’t be checked after each single test.) | int | 0 | false |
reuseExistingDescription | If true, the algorithm tries to find a good starting point close to an existing definition/super class of the given class in the knowledge base. | boolean | false | false |
replaceSearchTree | specifies whether to replace the search tree in the log file after each run or append the new search tree | boolean | false | false |
stopOnFirstDefinition | algorithm will terminate immediately when a correct definition is found | boolean | false | false |
maxClassExpressionTests | The maximum number of candidate hypothesis the algorithm is allowed to test (0 = no limit). The algorithm will stop afterwards. (The real number of tests can be slightly higher, because this criterion usually won’t be checked after each single test.) | int | 0 | false |
singleSuggestionMode | Use this if you are interested in only one suggestion and your learning problem has many (more than 1000) examples. | boolean | false | false |
maxNrOfResults | Sets the maximum number of results one is interested in. (Setting this to a lower value may increase performance as the learning algorithm has to store/evaluate/beautify less descriptions). | int | 10 | false |
ClassLearningProblem
short name: clp
version: 0.6
implements: LearningProblem
option name | description | type | default value | required? |
---|---|---|---|---|
accuracyMethod | Specifies, which method/function to use for computing accuracy. Available measues are “pred_acc” (predictive accuracy), “fmeasure” (F measure), “generalised_fmeasure” (generalised F-Measure according to Fanizzi and d’Amato). | String | pred_acc | false |
classToDescribe | class of which a description should be learned | NamedClass | true | |
checkConsistency | whether to check for consistency of suggestions (when added to ontology) | boolean | true | false |
approxDelta | The Approximate Delta | double | 0.05 | false |
betaSC | beta index for F-measure in super class learning | double | 3.0 | false |
betaEq | beta index for F-measure in definition learning | double | 1.0 | false |
useApproximations | Use Approximations | boolean | false | false |
Disjunctive ELTL
short name: deltl
version: 0.5
implements: LearningAlgorithm, ClassExpressionLearningAlgorithm
description: Disjunctive ELTL is an algorithm based on the refinement operator in http://jens-lehmann.org/files/2009/el_ilp.pdf with support for disjunctions.
option name | description | type | default value | required? |
---|---|---|---|---|
tryFullCoverage | If yes, then the algorithm tries to cover all positive examples. Note that while this improves accuracy on the testing set, it may lead to overfitting. | boolean | false | false |
treeSearchTimeSeconds | Specifies how long the algorithm should search for a partial solution (a tree). | double | 1.0 | false |
ELTL
short name: eltl
version: 0.5
implements: LearningAlgorithm, ClassExpressionLearningAlgorithm
description: ELTL is an algorithm based on the refinement operator in http://jens-lehmann.org/files/2009/el_ilp.pdf.
option name | description | type | default value | required? |
---|---|---|---|---|
instanceBasedDisjoints | Specifies whether to use real disjointness checks or instance based ones (no common instances) in the refinement operator. | boolean | true | false |
Fuzzy CELOE
short name: fceloe
version: 0.2
implements: LearningAlgorithm, ClassExpressionLearningAlgorithm
description: See Fuzzy DL-Learner paper published at ISDA 2011.
This component does not have configuration options.
Fuzzy OWL API Reasoner
short name: foar
version: 0.2
implements: ReasonerComponent
This component does not have configuration options.
FuzzyPosNegLPStandard
short name: fuzzyPosNeg
version: 0.2
implements: LearningProblem
This component does not have configuration options.
KB File
short name: kbfile
version: 0.8
implements: KnowledgeSource
option name | description | type | default value | required? |
---|---|---|---|---|
url | URL pointer to the KB file | String | false | |
fileName | relative or absolute path to KB file | String | false |
OEHeuristicRuntime
short name: celoe_heuristic
version: 0.5
implements: OtherComponent
option name | description | type | default value | required? |
---|---|---|---|---|
startNodeBonus | no description available | double | 0.1 | false |
OWL API Reasoner
short name: oar
version: 0.8
implements: ReasonerComponent
option name | description | type | default value | required? |
---|---|---|---|---|
reasonerType | The name of the OWL APIReasoner to use {“fact”, “hermit”, “owllink”, “pellet”, “elk”, “cel”} | String | pellet | false |
owlLinkURL | The URL to the owl server | String | false |
OWL Class Expression Learner
short name: ocel
version: 1.2
implements: LearningAlgorithm, ClassExpressionLearningAlgorithm
This component does not have configuration options.
OWL File
short name: owlfile
version: 0.9
implements: KnowledgeSource
This component does not have configuration options.
PCELOE
short name: pceloe
version: 1.0
implements: LearningAlgorithm, ClassExpressionLearningAlgorithm
description: CELOE is an adapted and extended version of the OCEL algorithm applied for the ontology engineering use case. See http://jens-lehmann.org/files/2011/celoe.pdf for reference.
option name | description | type | default value | required? |
---|---|---|---|---|
maxExecutionTimeInSecondsAfterImprovement | maximum execution of the algorithm in seconds | int | 0 | false |
startClass | You can specify a start class for the algorithm. To do this, you have to use Manchester OWL syntax without using prefixes. | Description | owl:Thing | false |
noisePercentage | the (approximated) percentage of noise within the examples | double | 0.0 | false |
nrOfThreads | number of threads running in parallel | int | 2 | false |
terminateOnNoiseReached | specifies whether to terminate when noise criterion is met | boolean | false | false |
writeSearchTree | specifies whether to write a search tree | boolean | false | false |
filterDescriptionsFollowingFromKB | If true, then the results will not contain suggestions, which already follow logically from the knowledge base. Be careful, since this requires a potentially expensive consistency check for candidate solutions. | boolean | false | false |
maxDepth | maximum depth of description | double | 7 | false |
searchTreeFile | file to use for the search tree | String | log/searchTree.txt | false |
maxExecutionTimeInSeconds | maximum execution of the algorithm in seconds | int | 10 | false |
useMinimizer | Specifies whether returned expressions should be minimised by removing those parts, which are not needed. (Basically the minimiser tries to find the shortest expression which is equivalent to the learned expression). Turning this feature off may improve performance. | boolean | true | false |
maxClassExpressionTestsAfterImprovement | The maximum number of candidate hypothesis the algorithm is allowed after an improvement in accuracy (0 = no limit). The algorithm will stop afterwards. (The real number of tests can be slightly higher, because this criterion usually won’t be checked after each single test.) | int | 0 | false |
reuseExistingDescription | If true, the algorithm tries to find a good starting point close to an existing definition/super class of the given class in the knowledge base. | boolean | false | false |
replaceSearchTree | specifies whether to replace the search tree in the log file after each run or append the new search tree | boolean | false | false |
maxClassExpressionTests | The maximum number of candidate hypothesis the algorithm is allowed to test (0 = no limit). The algorithm will stop afterwards. (The real number of tests can be slightly higher, because this criterion usually won’t be checked after each single test.) | int | 0 | false |
singleSuggestionMode | Use this if you are interested in only one suggestion and your learning problem has many (more than 1000) examples. | boolean | false | false |
maxNrOfResults | Sets the maximum number of results one is interested in. (Setting this to a lower value may increase performance as the learning algorithm has to store/evaluate/beautify less descriptions). | int | 10 | false |
PosNegLPStandard
short name: posNegStandard
version: 0.8
implements: LearningProblem
option name | description | type | default value | required? |
---|---|---|---|---|
approxDelta | The Approximate Delta | double | 0.05 | false |
accuracyMethod | Specifies, which method/function to use for computing accuracy. Available measues are “pred_acc” (predictive accuracy), “fmeasure” (F measure), “generalised_fmeasure” (generalised F-Measure according to Fanizzi and d’Amato). | String | predacc | false |
useApproximations | Use Approximations | boolean | false | false |
PosNegLPStrict
short name: posNegStrict
version: 0.8
implements: LearningProblem
option name | description | type | default value | required? |
---|---|---|---|---|
errorPenalty | penalty for errors (example can be inferred to belong to the negated concept class) | double | 3 | false |
accuracyPenalty | penalty for incorrectness (example belongs neither to concept nor its negation) | double | 1 | false |
Random Guesser
short name: randomGuesser
version: 0.8
implements: LearningAlgorithm, ClassExpressionLearningAlgorithm
This component does not have configuration options.
SPARQL endpoint
short name: sparql
version: 0.2
implements: KnowledgeSource
option name | description | type | default value | required? |
---|---|---|---|---|
url | no description available | URL | true | |
namedGraphs | no description available | List | [] | false |
defaultGraphs | no description available | List | [] | false |
SPARQL endpoint fragment
short name: sparqlfrag
version: 0.5
implements: KnowledgeSource
This component does not have configuration options.
data subPropertyOf axiom learner
short name: dplsubprop
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | DatatypeProperty | false |
dataproperty domain axiom learner
short name: dpldomain
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | DatatypeProperty | false |
dataproperty range learner
short name: dblrange
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | DatatypeProperty | false |
disjoint classes learner
short name: cldisjoint
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm, ClassExpressionLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
classToDescribe | NamedClass | false |
disjoint dataproperty axiom learner
short name: dpldisjoint
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | DatatypeProperty | false |
disjoint objectproperty axiom learner
short name: opldisjoint
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |
efficient SPARQL fragment extractor
short name: sparqls
version: 0.1
implements: KnowledgeSource
option name | description | type | default value | required? |
---|---|---|---|---|
aboxfilter | Filter for the tbox, can use variable ?s, ?p amd ?o | String | false | |
defaultGraphURI | default graph URI | String | true | |
ontologySchemaUrls | List of Ontology Schema URLs | List | true | |
sparqlQuery | Sparql Query | String | false | |
tboxfilter | Filter for the tbox, can use variable ?example and ?class | String | false | |
recursionDepth | recursion depth | int | true | |
endpointURL | URL of the SPARQL endpoint | String | true | |
instances | List of the instances to use | List | true |
equivalent dataproperty axiom learner
short name: dplequiv
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | DatatypeProperty | false |
equivalent objectproperty axiom learner
short name: oplequiv
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |
fast instance checker
short name: fic
version: 0.9
implements: ReasonerComponent
option name | description | type | default value | required? |
---|---|---|---|---|
forAllRetrievalSemantics | This option controls how to interpret the all quantifier in forall r.C. The standard option isto return all those which do not have an r-filler not in C. The domain semantics is to use thosewhich are in the domain of r and do not have an r-filler not in C. The forallExists semantics is touse those which have at least one r-filler and do not have an r-filler not in C. | String | standard | false |
defaultNegation | Whether to use default negation, i.e. an instance not being in a class means that it is in the negation of the class. | boolean | true | false |
functional dataproperty axiom learner
short name: dplfunc
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | DatatypeProperty | false |
functional objectproperty axiom learner
short name: oplfunc
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |
inversefunctional objectproperty axiom learner
short name: oplinvfunc
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |
multiple criteria heuristic
short name: multiheuristic
version: 0.7
implements: OtherComponent
option name | description | type | default value | required? |
---|---|---|---|---|
expansionPenaltyFactor | no description available | double | 0.02 | false |
negativeWeight | no description available | double | 1.0 | false |
startNodeBonus | no description available | double | 0.1 | false |
negationPenalty | no description available | int | 0 | false |
gainBonusFactor | no description available | double | 0.5 | false |
nodeChildPenalty | no description available | double | 0.0001 | false |
object subPropertyOf axiom learner
short name: oplsubprop
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |
objectproperty domain axiom learner
short name: opldomain
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |
objectproperty range learner
short name: oplrange
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |
positive only learning problem
short name: posonlylp
version: 0.6
implements: LearningProblem
This component does not have configuration options.
rho refinement operator
short name: rho
version: 0.8
implements: RefinementOperator
option name | description | type | default value | required? |
---|---|---|---|---|
instanceBasedDisjoints | no description available | boolean | true | false |
useStringDatatypes | no description available | boolean | false | false |
useNegation | no description available | boolean | true | false |
useAllConstructor | no description available | boolean | true | false |
disjointChecks | no description available | boolean | true | false |
applyExistsFilter | no description available | boolean | true | false |
useHasValueConstructor | no description available | boolean | false | false |
useBooleanDatatypes | no description available | boolean | true | false |
useExistsConstructor | no description available | boolean | true | false |
dropDisjuncts | no description available | boolean | false | false |
applyAllFilter | no description available | boolean | true | false |
useDoubleDatatypes | no description available | boolean | true | false |
useCardinalityRestrictions | no description available | boolean | true | false |
simple subclass learner
short name: clsub
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm, ClassExpressionLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
classToDescribe | NamedClass | true |
symmetric objectproperty axiom learner
short name: oplsymm
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |
synchronized rho refinement operator
short name: syncrho
version: 0.8
implements: RefinementOperator
option name | description | type | default value | required? |
---|---|---|---|---|
instanceBasedDisjoints | no description available | boolean | true | false |
useStringDatatypes | no description available | boolean | false | false |
useNegation | no description available | boolean | true | false |
useAllConstructor | no description available | boolean | true | false |
disjointChecks | no description available | boolean | true | false |
applyExistsFilter | no description available | boolean | true | false |
useHasValueConstructor | no description available | boolean | false | false |
useBooleanDatatypes | no description available | boolean | true | false |
useExistsConstructor | no description available | boolean | true | false |
dropDisjuncts | no description available | boolean | false | false |
applyAllFilter | no description available | boolean | true | false |
useDoubleDatatypes | no description available | boolean | true | false |
useCardinalityRestrictions | no description available | boolean | true | false |
transitive objectproperty axiom learner
short name: opltrans
version: 0.1
implements: LearningAlgorithm, AxiomLearningAlgorithm
option name | description | type | default value | required? |
---|---|---|---|---|
propertyToDescribe | ObjectProperty | false |