Terrier IR Platform
2.2.1

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

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

Terrier IR Platform
2.2.1

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