uk.ac.gla.terrier.matching.models
Class DFR_BM25

java.lang.Object
  uk.ac.gla.terrier.matching.models.WeightingModel
      uk.ac.gla.terrier.matching.models.DFR_BM25

All Implemented Interfaces:

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

public class DFR_BM25
extends WeightingModel

This class implements the DFR_BM25 weighting model. This DFR model, if expanded in Taylor's series, provides the BM25 formula, when the parameter c is set to 1.

Version:

$Revision: 1.15 $

Author:

Gianni Amati, Ben He

See Also:

Serialized Form

Constructor Summary

DFR_BM25()
A default constructor.

DFR_BM25(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) Computes the score according to the model DFR_BM25.
double	score(double tf, double docLength, double documentFrequency, double termFrequency, double keyFrequency) Computes the score according to the model DFR_BM25.

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

DFR_BM25

public DFR_BM25()

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

DFR_BM25

public DFR_BM25(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)

Computes the score according to the model DFR_BM25.

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)

Computes the score according to the model DFR_BM25.

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.