@Reference(authors="Bagga, A. and Baldwin, B.", title="Entity-based cross-document coreferencing using the Vector Space Model", booktitle="Proc. COLING \'98 Proceedings of the 17th international conference on Computational linguistics", url="http://dx.doi.org/10.3115/980451.980859") public class ClusteringBCubedF1SimilarityFunction extends AbstractPrimitiveSimilarityFunction<Clustering<?>> implements ClusteringDistanceSimilarityFunction, NormalizedSimilarityFunction<Clustering<?>>
Bagga, A. and Baldwin, B.
Entity-based cross-document coreferencing using the Vector Space Model
Proc. COLING '98 Proceedings of the 17th international conference on
Computational linguistics
| Modifier and Type | Class and Description |
|---|---|
static class |
ClusteringBCubedF1SimilarityFunction.Parameterizer
Parameterization class.
|
| Modifier and Type | Field and Description |
|---|---|
static ClusteringBCubedF1SimilarityFunction |
STATIC
Static instance.
|
| Constructor and Description |
|---|
ClusteringBCubedF1SimilarityFunction()
Constructor - use the static instance
STATIC! |
| Modifier and Type | Method and Description |
|---|---|
double |
distance(Clustering<?> o1,
Clustering<?> o2)
Computes the distance between two given DatabaseObjects according to this
distance function.
|
SimpleTypeInformation<? super Clustering<?>> |
getInputTypeRestriction()
Get the input data type of the function.
|
<T extends Clustering<?>> |
instantiate(Relation<T> relation)
Instantiate with a representation to get the actual similarity query.
|
boolean |
isMetric()
Is this distance function metric (in particular, does it satisfy the
triangle equation?)
|
double |
similarity(Clustering<?> o1,
Clustering<?> o2)
Computes the similarity between two given DatabaseObjects according to this
similarity function.
|
isSymmetricclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitisSymmetricisSymmetricpublic static final ClusteringBCubedF1SimilarityFunction STATIC
public ClusteringBCubedF1SimilarityFunction()
STATIC!public double similarity(Clustering<?> o1, Clustering<?> o2)
PrimitiveSimilarityFunctionsimilarity in interface PrimitiveSimilarityFunction<Clustering<?>>similarity in class AbstractPrimitiveSimilarityFunction<Clustering<?>>o1 - first DatabaseObjecto2 - second DatabaseObjectpublic double distance(Clustering<?> o1, Clustering<?> o2)
PrimitiveDistanceFunctiondistance in interface PrimitiveDistanceFunction<Clustering<?>>o1 - first DatabaseObjecto2 - second DatabaseObjectpublic boolean isMetric()
DistanceFunctionisMetric in interface DistanceFunction<Clustering<?>>true when metric.public <T extends Clustering<?>> DistanceSimilarityQuery<T> instantiate(Relation<T> relation)
SimilarityFunctioninstantiate in interface DistanceFunction<Clustering<?>>instantiate in interface ClusteringDistanceSimilarityFunctioninstantiate in interface SimilarityFunction<Clustering<?>>instantiate in class AbstractPrimitiveSimilarityFunction<Clustering<?>>relation - Representation to usepublic SimpleTypeInformation<? super Clustering<?>> getInputTypeRestriction()
SimilarityFunctiongetInputTypeRestriction in interface DistanceFunction<Clustering<?>>getInputTypeRestriction in interface PrimitiveDistanceFunction<Clustering<?>>getInputTypeRestriction in interface PrimitiveSimilarityFunction<Clustering<?>>getInputTypeRestriction in interface SimilarityFunction<Clustering<?>>getInputTypeRestriction in class AbstractPrimitiveSimilarityFunction<Clustering<?>>Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.