Terrier IR Platform
2.2.1

uk.ac.gla.terrier.matching.models
Class IFB2

java.lang.Object
  extended by uk.ac.gla.terrier.matching.models.WeightingModel
      extended by uk.ac.gla.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.

Version:
$Revision: 1.19 $
Author:
Gianni Amati, Ben He, Vassilis Plachouras
See Also:
Serialized Form

Constructor Summary
IFB2()
          A default constructor.
IFB2(double c)
          Constructs an instance of this class with the specified value for the parameter c.
 
Method Summary
 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.
 double score(double tf, double docLength, double n_t, double F_t, double keyFrequency)
          Uses IFB2 to compute a weight for a term in a document.
 
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

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

score

public final double score(double tf,
                          double docLength,
                          double n_t,
                          double F_t,
                          double keyFrequency)
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
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 assigned by the weighting model IFB2.

Terrier IR Platform
2.2.1

Terrier Information Retrieval Platform 2.2.1. Copyright 2004-2008 University of Glasgow