org.terrier.matching.models

Class LemurTF_IDF

java.lang.Object

org.terrier.matching.models.WeightingModel

org.terrier.matching.models.LemurTF_IDF

All Implemented Interfaces:

Serializable, 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, cs, documentFrequency, es, i, keyFrequency, numberOfDocuments, numberOfPointers, numberOfTokens, numberOfUniqueTerms, rq, termFrequency

Constructor Summary

Constructors

Constructor and Description
LemurTF_IDF() A default constructor.

Method Summary

Methods

Modifier and Type	Method and Description
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) Deprecated.

Methods inherited from class org.terrier.matching.models.WeightingModel

clone, getOverflowed, getParameter, prepare, score, setCollectionStatistics, setEntryStatistics, setKeyFrequency, setParameter, setRequest

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 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

@Deprecated
public final double score(double tf,
                      double docLength,
                      double documentFrequency,
                      double termFrequency,
                      double keyFrequency)

Deprecated.

This method provides the contract for implementing weighting models. As of Terrier 3.6, the 5-parameter score method is being deprecated since it is not used. The two parameter score method should be used instead. Tagged for removal in a later version.

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.