gov.sandia.cognition.text.term.relation

Class TermVectorSimilarityNetworkCreator

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.text.term.relation.TermVectorSimilarityNetworkCreator

All Implemented Interfaces:

CloneableSerializable, java.io.Serializable, java.lang.Cloneable

public class TermVectorSimilarityNetworkCreator
extends AbstractCloneableSerializable

Creates term similarity networks by comparing vectors representing the terms.

Since:

3.0

Author:

Justin Basilico

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_EFFECTIVE_ZERO The default effective zero value is 0.0.
protected double	effectiveZero The value to treat as zero.
protected MatrixFactory<? extends Matrix>	matrixFactory The matrix factory to create the matrix that backs the similarity network.
protected SimilarityFunction<? super Vector,? super Vector>	similarityFunction The similarity function between term vectors used to determine the similarity between two terms.

Constructor Summary

Constructors

Constructor and Description
TermVectorSimilarityNetworkCreator() Creates a new TermVectorSimilarityNetworkCreator.
TermVectorSimilarityNetworkCreator(SimilarityFunction<? super Vector,? super Vector> similarityFunction) Creates a new TermVectorSimilarityNetworkCreator.
TermVectorSimilarityNetworkCreator(SimilarityFunction<? super Vector,? super Vector> similarityFunction, double effectiveZero) Creates a new TermVectorSimilarityNetworkCreator.
TermVectorSimilarityNetworkCreator(SimilarityFunction<? super Vector,? super Vector> similarityFunction, double effectiveZero, MatrixFactory<? extends Matrix> matrixFactory) Creates a new TermVectorSimilarityNetworkCreator.

Method Summary

Modifier and Type	Method and Description
MatrixBasedTermSimilarityNetwork	create(java.util.Collection<? extends Vectorizable> documents, TermIndex termIndex) Creates a new similarity network between the terms in the given documents.
double	getEffectiveZero() Gets the value to treat as zero.
MatrixFactory<? extends Matrix>	getMatrixFactory() Gets the matrix factory to create the matrix that backs the similarity network.
SimilarityFunction<? super Vector,? super Vector>	getSimilarityFunction() Gets the similarity function between term vectors used to determine the similarity between two terms.
void	setEffectiveZero(double effectiveZero) Sets the value to treat as zero.
void	setMatrixFactory(MatrixFactory<? extends Matrix> matrixFactory) Sets the matrix factory to create the matrix that backs the similarity network.
void	setSimilarityFunction(SimilarityFunction<? super Vector,? super Vector> similarityFunction) Sets the similarity function between term vectors used to determine the similarity between two terms.

Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable

clone

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

DEFAULT_EFFECTIVE_ZERO

public static final double DEFAULT_EFFECTIVE_ZERO

The default effective zero value is 0.0.

See Also:

Constant Field Values

similarityFunction

protected SimilarityFunction<? super Vector,? super Vector> similarityFunction

The similarity function between term vectors used to determine the similarity between two terms.

effectiveZero

protected double effectiveZero

The value to treat as zero. Used to increase the sparseness of a similarity network.

matrixFactory

protected MatrixFactory<? extends Matrix> matrixFactory

The matrix factory to create the matrix that backs the similarity network.

Constructor Detail

TermVectorSimilarityNetworkCreator

public TermVectorSimilarityNetworkCreator()

Creates a new TermVectorSimilarityNetworkCreator.

TermVectorSimilarityNetworkCreator

public TermVectorSimilarityNetworkCreator(SimilarityFunction<? super Vector,? super Vector> similarityFunction)

Creates a new TermVectorSimilarityNetworkCreator.

Parameters:

similarityFunction - The similarity function between term vectors used to determine the term similarity.

TermVectorSimilarityNetworkCreator

public TermVectorSimilarityNetworkCreator(SimilarityFunction<? super Vector,? super Vector> similarityFunction,
                                          double effectiveZero)

Creates a new TermVectorSimilarityNetworkCreator.

Parameters:

similarityFunction - The similarity function between term vectors used to determine the term similarity.

effectiveZero - The effective value to treat as zero. Used to increase the sparseness of a similarity network.

TermVectorSimilarityNetworkCreator

public TermVectorSimilarityNetworkCreator(SimilarityFunction<? super Vector,? super Vector> similarityFunction,
                                          double effectiveZero,
                                          MatrixFactory<? extends Matrix> matrixFactory)

Creates a new TermVectorSimilarityNetworkCreator.

Parameters:

similarityFunction - The similarity function between term vectors used to determine the term similarity.

effectiveZero - The effective value to treat as zero. Used to increase the sparseness of a similarity network.

matrixFactory - The matrix factory used to create the similarity matrix.

Method Detail

create

public MatrixBasedTermSimilarityNetwork create(java.util.Collection<? extends Vectorizable> documents,
                                               TermIndex termIndex)

Creates a new similarity network between the terms in the given documents. First the document vectors are turned into a term-by-document matrix. Then the similarity function in this object is used to calculate the similarity between the column vectors representing each term to populate a term-by-term matrix. The resulting matrix will be symmetric.

Parameters:

documents - The term vectors for each document to calculate the similarity network from.

termIndex - The index of terms that was used to create the term vectors for each document.

Returns:

A new similarity network for the terms in the given index calculated using the given vectors.

getSimilarityFunction

public SimilarityFunction<? super Vector,? super Vector> getSimilarityFunction()

Gets the similarity function between term vectors used to determine the similarity between two terms.

Returns:

The similarity function.

setSimilarityFunction

public void setSimilarityFunction(SimilarityFunction<? super Vector,? super Vector> similarityFunction)

Sets the similarity function between term vectors used to determine the similarity between two terms.

Parameters:

similarityFunction - The similarity function.

getEffectiveZero

public double getEffectiveZero()

Gets the value to treat as zero. Used to increase the sparseness of a similarity network.

Returns:

The threshold to treat absolute values below as zero.

setEffectiveZero

public void setEffectiveZero(double effectiveZero)

Sets the value to treat as zero. Used to increase the sparseness of a similarity network.

Parameters:

effectiveZero - The threshold to treat absolute values below as zero.

getMatrixFactory

public MatrixFactory<? extends Matrix> getMatrixFactory()

Gets the matrix factory to create the matrix that backs the similarity network.

Returns:

The matrix factory.

setMatrixFactory

public void setMatrixFactory(MatrixFactory<? extends Matrix> matrixFactory)

Sets the matrix factory to create the matrix that backs the similarity network.

Parameters:

matrixFactory - The matrix factory.