uk.ac.gla.terrier.matching.models
Class In_expB2

java.lang.Object
  uk.ac.gla.terrier.matching.models.WeightingModel
      uk.ac.gla.terrier.matching.models.In_expB2

All Implemented Interfaces:

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

public class In_expB2
extends WeightingModel

This class implements the PL2 weighting model.

Version:

$Revision: 1.18 $

Author:

Gianni Amati, Ben He, Vassilis Plachouras

See Also:

Serialized Form

Constructor Summary

In_expB2()
A default constructor.

In_expB2(double c)
Constructs an instance of this class with the specified value for the parameter beta.

Method Summary

java.lang.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) This method provides the contract for implementing weighting models.

Methods inherited from class uk.ac.gla.terrier.matching.models.WeightingModel

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

Methods inherited from class java.lang.Object

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

Constructor Detail

In_expB2

public In_expB2()

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

In_expB2

public In_expB2(double c)

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

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)

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 final double score(double tf,
                          double docLength,
                          double documentFrequency,
                          double termFrequency,
                          double keyFrequency)

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

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.