org.terrier.matching.models.queryexpansion
Class KLCorrect

java.lang.Object
  org.terrier.matching.models.queryexpansion.QueryExpansionModel
      org.terrier.matching.models.queryexpansion.KLCorrect

public class KLCorrect
extends QueryExpansionModel

This class implements the correct Kullback-Leibler divergence for query expansion, which takes the contribution into consideration. See the equation before (8.13), page 149.

Author:

Gianni Amati, Ben He, Vassilis Plachouras

Field Summary

Fields inherited from class org.terrier.matching.models.queryexpansion.QueryExpansionModel

averageDocumentLength, collectionLength, documentFrequency, EXPANSION_DOCUMENTS, EXPANSION_TERMS, idf, maxTermFrequency, numberOfDocuments, PARAMETER_FREE, ROCCHIO_BETA, totalDocumentLength

Constructor Summary

KLCorrect()
A default constructor.

Method Summary

java.lang.String	getInfo() Returns the name of the model.
double	parameterFreeNormaliser() This method provides the contract for computing the normaliser of parameter-free query expansion.
double	parameterFreeNormaliser(double maxTermFrequency, double collectionLength, double totalDocumentLength) This method provides the contract for computing the normaliser of parameter-free query expansion.
double	score(double withinDocumentFrequency, double termFrequency) This method implements the query expansion model.
double	score(double withinDocumentFrequency, double termFrequency, double totalDocumentLength, double collectionLength, double averageDocumentLength) This method implements the query expansion model.

Methods inherited from class org.terrier.matching.models.queryexpansion.QueryExpansionModel

initialise, setAverageDocumentLength, setCollectionLength, setDocumentFrequency, setMaxTermFrequency, setNumberOfDocuments, setTotalDocumentLength

Methods inherited from class java.lang.Object

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

Constructor Detail

KLCorrect

public KLCorrect()

A default constructor.

Method Detail

getInfo

public final java.lang.String getInfo()

Returns the name of the model.

Specified by:

getInfo in class QueryExpansionModel

Returns:

the name of the model

parameterFreeNormaliser

public final double parameterFreeNormaliser()

This method provides the contract for computing the normaliser of parameter-free query expansion.

Specified by:

parameterFreeNormaliser in class QueryExpansionModel

Returns:

The normaliser.

parameterFreeNormaliser

public final double parameterFreeNormaliser(double maxTermFrequency,
                                            double collectionLength,
                                            double totalDocumentLength)

This method provides the contract for computing the normaliser of parameter-free query expansion.

Specified by:

parameterFreeNormaliser in class QueryExpansionModel

Parameters:

maxTermFrequency - The maximum of the in-collection term frequency of the terms in the pseudo relevance set.

collectionLength - The number of tokens in the collections.

totalDocumentLength - The sum of the length of the top-ranked documents.

Returns:

The normaliser.

score

public final double score(double withinDocumentFrequency,
                          double termFrequency)

This method implements the query expansion model.

Specified by:

score in class QueryExpansionModel

Parameters:

withinDocumentFrequency - double The term frequency in the X top-retrieved documents.

termFrequency - double The term frequency in the collection.

Returns:

double The query expansion weight using he complete Kullback-Leibler divergence.

score

public final double score(double withinDocumentFrequency,
                          double termFrequency,
                          double totalDocumentLength,
                          double collectionLength,
                          double averageDocumentLength)

This method implements the query expansion model.

Specified by:

score in class QueryExpansionModel

Parameters:

withinDocumentFrequency - double The term frequency in the X top-retrieved documents.

termFrequency - double The term frequency in the collection.

totalDocumentLength - double The sum of length of the X top-retrieved documents.

collectionLength - double The number of tokens in the whole collection.

averageDocumentLength - double The average document length in the collection.

Returns:

double The score returned by the implemented model.