org.terrier.matching.models
Class DFR_BM25

java.lang.Object
  extended by org.terrier.matching.models.WeightingModel
      extended by org.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.

Author:
Gianni Amati, Ben He
See Also:
Serialized Form

Field Summary
 
Fields inherited from class org.terrier.matching.models.WeightingModel
averageDocumentLength, c, documentFrequency, i, keyFrequency, numberOfDocuments, numberOfPointers, numberOfTokens, numberOfUniqueTerms, termFrequency
 
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 org.terrier.matching.models.WeightingModel
clone, getOverflowed, getParameter, prepare, score, setAverageDocumentLength, setCollectionStatistics, setDocumentFrequency, setEntryStatistics, setKeyFrequency, setNumberOfDocuments, setNumberOfPointers, setNumberOfTokens, setNumberOfUniqueTerms, setParameter, setRequest, setTermFrequency, stirlingPower
 
Methods inherited from class java.lang.Object
equals, finalize, 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.


Terrier 3.5. Copyright © 2004-2011 University of Glasgow