Package org.terrier.matching.models

Class IFB2

java.lang.Object

org.terrier.matching.models.WeightingModel

org.terrier.matching.models.IFB2

All Implemented Interfaces:

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

public class IFB2
extends WeightingModel

This class implements the IFB2 weighting model.

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, numberOfPostings, numberOfTokens, numberOfUniqueTerms, rq, termFrequency

Constructor Summary

Constructors

Constructor	Description
IFB2()	A default constructor.
IFB2(double c)	Constructs an instance of this class with the specified value for the parameter c.

Method Summary

Modifier and Type	Method	Description
java.lang.String	getInfo()	Returns the name of the model.
double	score(double tf, double docLength)	Uses IFB2 to compute a weight for a term in a document.

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

IFB2

public IFB2()

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

IFB2

public IFB2(double c)

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

Parameters:

c - the term frequency normalisation parameter value.

Method Detail

getInfo

public final java.lang.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)

Uses IFB2 to compute a weight for a term in a document.

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