/*
* Carrot2 project.
*
* Copyright (C) 2002-2014, Dawid Weiss, Stanisław Osiński.
* All rights reserved.
*
* Refer to the full license file "carrot2.LICENSE"
* in the root folder of the repository checkout or at:
* http://www.carrot2.org/carrot2.LICENSE
*/
package org.carrot2.text.vsm;
import org.apache.mahout.math.matrix.DoubleMatrix2D;
import org.apache.mahout.math.matrix.impl.DenseDoubleMatrix2D;
import org.carrot2.core.attribute.Processing;
import org.carrot2.matrix.MatrixUtils;
import org.carrot2.matrix.factorization.IMatrixFactorization;
import org.carrot2.matrix.factorization.IMatrixFactorizationFactory;
import org.carrot2.matrix.factorization.IterationNumberGuesser;
import org.carrot2.matrix.factorization.IterationNumberGuesser.FactorizationQuality;
import org.carrot2.matrix.factorization.IterativeMatrixFactorizationFactory;
import org.carrot2.matrix.factorization.KMeansMatrixFactorizationFactory;
import org.carrot2.matrix.factorization.LocalNonnegativeMatrixFactorizationFactory;
import org.carrot2.matrix.factorization.NonnegativeMatrixFactorizationEDFactory;
import org.carrot2.matrix.factorization.NonnegativeMatrixFactorizationKLFactory;
import org.carrot2.matrix.factorization.PartialSingularValueDecompositionFactory;
import org.carrot2.util.attribute.Attribute;
import org.carrot2.util.attribute.AttributeLevel;
import org.carrot2.util.attribute.Bindable;
import org.carrot2.util.attribute.Group;
import org.carrot2.util.attribute.Input;
import org.carrot2.util.attribute.Label;
import org.carrot2.util.attribute.Level;
import org.carrot2.util.attribute.Required;
import org.carrot2.util.attribute.constraint.ImplementingClasses;
/**
* Reduces the dimensionality of a term-document matrix using a matrix factorization
* algorithm.
*/
@SuppressWarnings("deprecation")
@Bindable(prefix = "TermDocumentMatrixReducer")
public class TermDocumentMatrixReducer
{
/**
* Factorization method. The method to be used to factorize the term-document matrix
* and create base vectors that will give rise to cluster labels.
*/
@Input
@Processing
@Attribute
@Required
@ImplementingClasses(classes =
{
PartialSingularValueDecompositionFactory.class,
NonnegativeMatrixFactorizationEDFactory.class,
NonnegativeMatrixFactorizationKLFactory.class,
LocalNonnegativeMatrixFactorizationFactory.class,
KMeansMatrixFactorizationFactory.class
}, strict = false)
@Label("Factorization method")
@Level(AttributeLevel.ADVANCED)
@Group(TermDocumentMatrixBuilder.MATRIX_MODEL)
public IMatrixFactorizationFactory factorizationFactory = new NonnegativeMatrixFactorizationEDFactory();
/**
* Factorization quality. The number of iterations of matrix factorization to perform.
* The higher the required quality, the more time-consuming clustering.
*/
@Input
@Processing
@Required
@Attribute
@Label("Factorization quality")
@Level(AttributeLevel.ADVANCED)
@Group(TermDocumentMatrixBuilder.MATRIX_MODEL)
public FactorizationQuality factorizationQuality = FactorizationQuality.HIGH;
/**
* Performs the reduction.
*/
public void reduce(ReducedVectorSpaceModelContext context, int dimensions)
{
final VectorSpaceModelContext vsmContext = context.vsmContext;
if (vsmContext.termDocumentMatrix.columns() == 0
|| vsmContext.termDocumentMatrix.rows() == 0)
{
context.baseMatrix = new DenseDoubleMatrix2D(
vsmContext.termDocumentMatrix.rows(),
vsmContext.termDocumentMatrix.columns());
return;
}
if (factorizationFactory instanceof IterativeMatrixFactorizationFactory)
{
((IterativeMatrixFactorizationFactory) factorizationFactory).setK(dimensions);
IterationNumberGuesser.setEstimatedIterationsNumber(
(IterativeMatrixFactorizationFactory) factorizationFactory,
vsmContext.termDocumentMatrix, factorizationQuality);
}
MatrixUtils.normalizeColumnL2(vsmContext.termDocumentMatrix, null);
final IMatrixFactorization factorization = factorizationFactory
.factorize(vsmContext.termDocumentMatrix);
context.baseMatrix = factorization.getU();
context.coefficientMatrix = factorization.getV();
context.baseMatrix = trim(factorization.getU(), dimensions);
context.coefficientMatrix = trim(factorization.getV(), dimensions);
}
private final DoubleMatrix2D trim(DoubleMatrix2D matrix, int dimensions)
{
if (!(factorizationFactory instanceof IterativeMatrixFactorizationFactory)
&& matrix.columns() > dimensions)
{
return matrix.viewPart(0, 0, matrix.rows(), dimensions);
}
else
{
return matrix;
}
}
}