org.terrier.matching.models

Class InB2

java.lang.Object

org.terrier.matching.models.WeightingModel

org.terrier.matching.models.InB2

All Implemented Interfaces:

Serializable, Cloneable, Model

public class InB2
extends WeightingModel

This class implements the InB2 weighting model, namely Inverse Document Frequency model with Bernoulli after-effect and normalisation 2.

Author:

Gianni Amati, Ben He, Vassilis Plachouras

See Also:

Serialized Form

Field Summary

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

averageDocumentLength, c, cs, documentFrequency, es, i, keyFrequency, numberOfDocuments, numberOfPointers, numberOfTokens, numberOfUniqueTerms, rq, termFrequency

Constructor Summary

Constructors

Constructor and Description
InB2() A default constructor.
InB2(double c) Constructs an instance of this class with the specified value for the parameter c

Method Summary

Methods

Modifier and Type	Method and Description
String	getInfo() Returns the name of the model.
double	score(double tf, double docLength) This method provides the contract for implementing weighting models.
double	score(double tf, double docLength, double documentFrequency, double termFrequency, double keyFrequency) Deprecated.

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

clone, getOverflowed, getParameter, prepare, score, setCollectionStatistics, setEntryStatistics, setKeyFrequency, setParameter, setRequest

Methods inherited from class java.lang.Object

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

Constructor Detail

InB2

public InB2()

A default constructor. This must be followed by specifying the c value.

InB2

public InB2(double c)

Constructs an instance of this class with the specified value for the parameter c

Parameters:

c - double the term frequency normalisation parameter value.

Method Detail

getInfo

public final String getInfo()

Returns the name of the model.

Specified by:

getInfo in interface Model

Specified by:

getInfo in class WeightingModel

Returns:

the name of the model

score

public final double score(double tf,
           double docLength)

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

@Deprecated
public final double score(double tf,
                      double docLength,
                      double documentFrequency,
                      double termFrequency,
                      double keyFrequency)

Deprecated.

This method provides the contract for implementing weighting models. As of Terrier 3.6, the 5-parameter score method is being deprecated since it is not used. The two parameter score method should be used instead. Tagged for removal in a later version.

Specified by:

score in class WeightingModel

Parameters:

tf - The term frequency in the document

docLength - the document's length

documentFrequency - The document frequency of the term

termFrequency - the term frequency in the collection

keyFrequency - the term frequency in the query

Returns:

the score returned by the implemented weighting model.