org.terrier.matching.models
Class LemurTF_IDF

java.lang.Object
  extended by org.terrier.matching.models.WeightingModel
      extended by org.terrier.matching.models.LemurTF_IDF
All Implemented Interfaces:
java.io.Serializable, java.lang.Cloneable, Model

public class LemurTF_IDF
extends WeightingModel

This class implements the TF_IDF weighting model as it is implemented in Lemur. See Notes on the Lemur TFIDF model. Chenxiang Zhai, 2001.

Author:
Ben He, Gianni Amati, Vassilis Plachouras
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
LemurTF_IDF()
          A default constructor.
 
Method Summary
 java.lang.String getInfo()
          Returns the name of the model.
 double score(double tf, double docLength)
          Uses LemurTF_IDF to compute a weight for a term in a document.
 double score(double tf, double docLength, double documentFrequency, double termFrequency, double keyFrequency)
          Uses LemurTF_IDF to compute a weight for a term in a document.
 
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

LemurTF_IDF

public LemurTF_IDF()
A default constructor. This must be followed by specifying the c 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 LemurTF_IDF 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 documentFrequency,
                          double termFrequency,
                          double keyFrequency)
Uses LemurTF_IDF 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
documentFrequency - The document frequency of the term
termFrequency - the term frequency in the collection
keyFrequency - the term frequency in the query
Returns:
the score assigned by the weighting model LemurTF_IDF.


Terrier 3.5. Copyright © 2004-2011 University of Glasgow