org.terrier.matching.models
Class PerFieldNormWeightingModel

java.lang.Object
  org.terrier.matching.models.WeightingModel
      org.terrier.matching.models.PerFieldNormWeightingModel

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Model

Direct Known Subclasses:

BM25F, PL2F

public class PerFieldNormWeightingModel
extends WeightingModel

A class for generating arbitrary per-field normalisation models. Per-field normalisation models are field-based models - i.e. they take into account the frequency of a term in each individual field of the document. In particular, they apply length normalisation on the frequency from each field, before using a linear combination of term frequencies to garner the final frequency.

Properties:

<ul>

w.fieldId (starting at 0)

c.fieldId (starting at 0)

Since:

3.0

Author:

Craig Macdonald

See Also:

Serialized Form

Field Summary

Fields inherited from class org.terrier.matching.models.WeightingModel

averageDocumentLength, c, documentFrequency, i, keyFrequency, numberOfDocuments, numberOfPointers, numberOfTokens, numberOfUniqueTerms, termFrequency

Constructor Summary

PerFieldNormWeightingModel(java.lang.Class<? extends BasicModel> _basicModel, java.lang.Class<? extends Normalisation> _normalisationModel)
Constructs an instance of PerFieldNormWeightingModel

PerFieldNormWeightingModel(java.lang.String[] parameters)
Constructs an instance of PerFieldNormWeightingModel

Method Summary

java.lang.String	getInfo() Returns the name of the model.
void	prepare() prepare
double	score(double tf, double docLength) This method provides the contract for implementing weighting models.
double	score(double tf, double docLength, double n_t, double F_t, double keyFrequency) This method provides the contract for implementing weighting models.
double	score(Posting _p) Returns score
void	setCollectionStatistics(CollectionStatistics _cs) Sets collection statistics
void	setEntryStatistics(EntryStatistics _es) Sets entry statistics.

Methods inherited from class org.terrier.matching.models.WeightingModel

clone, getOverflowed, getParameter, setAverageDocumentLength, setDocumentFrequency, setKeyFrequency, setNumberOfDocuments, setNumberOfPointers, setNumberOfTokens, setNumberOfUniqueTerms, setParameter, setRequest, setTermFrequency, stirlingPower

Methods inherited from class java.lang.Object

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

Constructor Detail

PerFieldNormWeightingModel

public PerFieldNormWeightingModel(java.lang.Class<? extends BasicModel> _basicModel,
                                  java.lang.Class<? extends Normalisation> _normalisationModel)
                           throws java.lang.Exception

Constructs an instance of PerFieldNormWeightingModel

Parameters:

_basicModel -

_normalisationModel -

Throws:

java.lang.Exception

PerFieldNormWeightingModel

public PerFieldNormWeightingModel(java.lang.String[] parameters)
                           throws java.lang.Exception

Constructs an instance of PerFieldNormWeightingModel

Parameters:

parameters -

Throws:

java.lang.Exception

Method Detail

prepare

public void prepare()

Description copied from class: WeightingModel

prepare

Overrides:

prepare in class WeightingModel

score

public double score(Posting _p)

Description copied from class: WeightingModel

Returns score

Overrides:

score in class WeightingModel

Returns:

score

setCollectionStatistics

public void setCollectionStatistics(CollectionStatistics _cs)

Description copied from class: WeightingModel

Sets collection statistics

Overrides:

setCollectionStatistics in class WeightingModel

setEntryStatistics

public void setEntryStatistics(EntryStatistics _es)

Description copied from class: WeightingModel

Sets entry statistics.

Overrides:

setEntryStatistics in class WeightingModel

getInfo

public java.lang.String getInfo()

Description copied from class: WeightingModel

Returns the name of the model.

Specified by:

getInfo in interface Model

Specified by:

getInfo in class WeightingModel

Returns:

java.lang.String

score

public double score(double tf,
                    double docLength)

Description copied from class: WeightingModel

This method provides the contract for implementing weighting models.

Specified by:

score in class WeightingModel

Parameters:

tf - The term frequency in the document

docLength - the document's length

Returns:

the score assigned to a document with the given tf and docLength, and other preset parameters

score

public double score(double tf,
                    double docLength,
                    double n_t,
                    double F_t,
                    double keyFrequency)

Description copied from class: WeightingModel

This method provides the contract for implementing weighting models.

Specified by:

score in class WeightingModel

Parameters:

tf - The term frequency in the document

docLength - the document's length

n_t - The document frequency of the term

F_t - the term frequency in the collection

keyFrequency - the term frequency in the query

Returns:

the score returned by the implemented weighting model.