Package org.carrot2.text.vsm

Class TermDocumentMatrixBuilder

java.lang.Object

org.carrot2.attrs.AttrComposite

org.carrot2.text.vsm.TermDocumentMatrixBuilder

All Implemented Interfaces:

AcceptingVisitor

public class TermDocumentMatrixBuilder
extends AttrComposite

Builds a term document matrix based on the provided PreprocessingContext.

Field Summary

Fields

Modifier and Type	Field	Description
AttrDouble	boostedFieldWeight	Gives more weight to words that appeared in title fields.
AttrStringArray	boostFields	Specifies a list of field names that are boosted by boostedFieldWeight attribute.
AttrInteger	maximumMatrixSize	Maximum term-document matrix size.
AttrDouble	maxWordDf	Maximum word document frequency.
TermWeighting	termWeighting	Term weighting.

Fields inherited from class org.carrot2.attrs.AttrComposite

attributes

Constructor Summary

Constructors

Constructor	Description
TermDocumentMatrixBuilder()

Method Summary

Modifier and Type	Method	Description
void	buildTermDocumentMatrix(VectorSpaceModelContext vsmContext)	Builds a term-document matrix from data provided in the context, stores the result in there.
void	buildTermPhraseMatrix(VectorSpaceModelContext context)	Builds a term-phrase matrix in the same space as the main term-document matrix.

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

Field Detail

boostedFieldWeight

public final AttrDouble boostedFieldWeight

Gives more weight to words that appeared in title fields. The larger the value, the stronger boost the title words will receive.

boostFields

public AttrStringArray boostFields

Specifies a list of field names that are boosted by boostedFieldWeight attribute. Content of fields provided in this attribute can be given more weight during clustering.

maximumMatrixSize

public final AttrInteger maximumMatrixSize

Maximum term-document matrix size. Determines the maximum number of the term-document matrix elements. The larger the size, the more accurate, time- and memory-consuming clustering.

maxWordDf

public final AttrDouble maxWordDf

Maximum word document frequency. The maximum document frequency allowed for words as a fraction of all documents. Words with document frequency larger than maxWordDf will be ignored. For example, when maxWordDf is 0.4, words appearing in more than 40% of documents will be be ignored. A value of 1.0 means that all words will be taken into account, no matter in how many documents they appear.

This attribute may be useful when certain words appear in most of the input documents (e.g. company name from header or footer) and such words dominate the cluster labels. In such case, setting it to a value lower than 1.0 (e.g. 0.9) may improve the clusters.

Another useful application of this attribute is when there is a need to generate only very specific clusters, that is clusters containing small numbers of documents. This can be achieved by setting maxWordDf to extremely low values: 0.1 or 0.05.

termWeighting

public TermWeighting termWeighting

Term weighting. The method for calculating weight of words in the term-document matrices.

Constructor Detail

TermDocumentMatrixBuilder

public TermDocumentMatrixBuilder()

Method Detail

buildTermDocumentMatrix

public void buildTermDocumentMatrix(VectorSpaceModelContext vsmContext)

Builds a term-document matrix from data provided in the context, stores the result in there.

buildTermPhraseMatrix

public void buildTermPhraseMatrix(VectorSpaceModelContext context)

Builds a term-phrase matrix in the same space as the main term-document matrix. If the processing context contains no phrases, VectorSpaceModelContext.termPhraseMatrix will remain null.