Package org.carrot2.clustering.lingo

Class UniqueLabelAssigner

java.lang.Object

org.carrot2.attrs.AttrComposite

org.carrot2.clustering.lingo.UniqueLabelAssigner

All Implemented Interfaces:

AcceptingVisitor, LabelAssigner

public class UniqueLabelAssigner
extends AttrComposite
implements LabelAssigner

Assigns unique labels to each base vector using a greedy algorithm. For each base vector chooses the label that maximizes the base vector--label term vector cosine similarity and has not been previously selected. Once a label is selected, it will not be used to label any other vector. This algorithm does not create duplicate cluster labels, which usually means that this assignment method will create more clusters than SimpleLabelAssigner. This method is slightly slower than SimpleLabelAssigner.

Field Summary

Fields inherited from class org.carrot2.attrs.AttrComposite

attributes

Constructor Summary

Constructors

Constructor	Description
UniqueLabelAssigner()

Method Summary

Modifier and Type	Method	Description
void	assignLabels(LingoProcessingContext context, org.carrot2.math.mahout.matrix.DoubleMatrix2D stemCos, com.carrotsearch.hppc.IntIntHashMap filteredRowToStemIndex, org.carrot2.math.mahout.matrix.DoubleMatrix2D phraseCos)	Assigns labels to base vectors found by the matrix factorization.

Methods inherited from class org.carrot2.attrs.AttrComposite

accept

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.carrot2.attrs.AcceptingVisitor

accept

Constructor Detail

UniqueLabelAssigner

public UniqueLabelAssigner()

Method Detail

assignLabels

public void assignLabels(LingoProcessingContext context,
                         org.carrot2.math.mahout.matrix.DoubleMatrix2D stemCos,
                         com.carrotsearch.hppc.IntIntHashMap filteredRowToStemIndex,
                         org.carrot2.math.mahout.matrix.DoubleMatrix2D phraseCos)

Description copied from interface: LabelAssigner

Assigns labels to base vectors found by the matrix factorization. The results must be stored in the LingoProcessingContext.clusterLabelFeatureIndex and LingoProcessingContext.clusterLabelScore arrays.

Specified by:

assignLabels in interface LabelAssigner

Parameters:

context - contains all information about the current clustering request

stemCos - base vector -- single stems cosine matrix

filteredRowToStemIndex - mapping between row indices of stemCos and indices of stems in PreprocessingContext.allStems

phraseCos - base vector -- phrase cosine matrix