Package | Description |
---|---|
fr.inrialpes.exmo.ontosim | |
fr.inrialpes.exmo.ontosim.align | |
fr.inrialpes.exmo.ontosim.string |
Modifier and Type | Class and Description |
---|---|
class |
NoAlignmentException |
Modifier and Type | Method and Description |
---|---|
double |
AlignmentGlobalSum.getMeasureValue(fr.inrialpes.exmo.ontowrap.LoadedOntology<?> o1,
fr.inrialpes.exmo.ontowrap.LoadedOntology<?> o2,
org.semanticweb.owl.align.Alignment al)
Similarity version of delta_gm issued from the Jerome Euzenat's paper
|
double |
ASAbstractCoverageTraversal.getValue(fr.inrialpes.exmo.ontowrap.Ontology<?> o1,
fr.inrialpes.exmo.ontowrap.Ontology<?> o2) |
double |
ASCoverageMeasure.getValue(fr.inrialpes.exmo.ontowrap.Ontology<?> o1,
fr.inrialpes.exmo.ontowrap.Ontology<?> o2) |
private void |
ASShortestPathMeasure.init()
This function does compute the values for all
|
java.util.Set<java.net.URI> |
ASAbstractCoverageTraversal.objectsToPreserve(fr.inrialpes.exmo.ontowrap.Ontology<?> o1) |
Modifier and Type | Method and Description |
---|---|
double |
JWNLDistances.basicGlossOverlap(java.lang.String s1,
java.lang.String s2)
Compute the overlap between all glosses of two strings
|
double |
JWNLDistances.basicSynonymySimilarity(java.lang.String s1,
java.lang.String s2)
Evaluate if two terms can be synonym
|
protected java.util.Collection<java.lang.String> |
JWNLDistances.computeGlossValue(java.lang.String s)
Cache method for glosses
|
protected java.util.Set<net.didion.jwnl.data.Synset> |
JWNLDistances.computeSynsets(java.lang.String s)
Cache method for synsets
|
double |
JWNLDistances.cosynonymySimilarity(java.lang.String s1,
java.lang.String s2)
Compute the proportion of common synset between two words
|
(package private) java.util.Set<net.didion.jwnl.data.Synset> |
JWNLDistances.getAllSenses(java.lang.String term)
Retrieve all WordNet senses of a term
|
void |
JWNLDistances.Initialize()
Initialize the JWNL API.
|
void |
JWNLDistances.Initialize(java.lang.String wordnetdir,
java.lang.String wordnetversion) |
double |
JWNLDistances.wuPalmerSimilarity(java.lang.String s1,
java.lang.String s2)
Compute the Wu-Palmer similarity defined by
score = 2*depth(lcs(s1,s2)) / (depth(s1) + depth(s2))
|
Constructor and Description |
---|
JWNLDistances() |
(C) INRIA, Univ. Grenoble Alpes & friends, 2008-2017