Terrier IR Platform
2.2.1

uk.ac.gla.terrier.matching.models.basicmodel
Class BM

java.lang.Object
  extended by uk.ac.gla.terrier.matching.models.basicmodel.BasicModel
      extended by uk.ac.gla.terrier.matching.models.basicmodel.BM
All Implemented Interfaces:
java.io.Serializable

public class BM
extends BasicModel

This class implements the BM weighting model, which generates the original weight given by the BM25 formula, without frequency normalisation and query term weighting. Feel free to combine the BM model with any frequency normalisation method. However, it is NOT recommended to use BM with the first normalisation for after effect. For example, to use the BM model with the normalisation 2, add the following line in file etc/trec.models: DFRWeightingModel(BM, , 2) Leave the space between the comas blank so that the first normalisation is disabled.

Version:
$Revision: 1.10 $
Author:
Ben He
See Also:
Serialized Form

Constructor Summary
BM()
          A default constructor.
 
Method Summary
 java.lang.String getInfo()
          Returns the name of the model.
 double score(double tf, double documentFrequency, double termFrequency, double keyFrequency, double documentLength)
          This method computes the score for the implemented weighting model.
 
Methods inherited from class uk.ac.gla.terrier.matching.models.basicmodel.BasicModel
setNumberOfDocuments, setNumberOfTokens, stirlingPower
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

BM

public BM()
A default constructor.

Method Detail

getInfo

public java.lang.String getInfo()
Returns the name of the model.

Specified by:
getInfo in class BasicModel
Returns:
the name of the model

score

public double score(double tf,
                    double documentFrequency,
                    double termFrequency,
                    double keyFrequency,
                    double documentLength)
This method computes the score for the implemented weighting model.

Specified by:
score in class BasicModel
Parameters:
tf - The term frequency in the document
documentFrequency - The document frequency of the term
termFrequency - the term frequency in the collection
keyFrequency - The normalised query term frequency.
documentLength - The length of the document.
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