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

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

All Implemented Interfaces:

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

public class Hiemstra_LM
extends WeightingModel

This class implements the Hiemstra LM weighting model. A default lambda value of 0.15 is used, according to section 5.2.3 of Djoerd Hiemstra's thesis: Using language models for information retrieval. PhD Thesis, Centre for Telematics and Information Technology, University of Twente, 2001.

Version:

$Revision: 1.8 $

Author:

Jie Peng

See Also:

Serialized Form

Constructor Summary

Hiemstra_LM()
A default constructor.

Hiemstra_LM(double lambda)
Constructs an instance of this class with the specified value for the parameter lambda.

Method Summary

java.lang.String	getInfo() Returns the name of the model.
double	score(double tf, double docLength) Uses Hiemestra_LM to compute a weight for a term in a document.
double	score(double tf, double docLength, double n_t, double F_t, double keyFrequency) Uses Hiemstra_LM to compute a weight for a term in a document.

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

Hiemstra_LM

public Hiemstra_LM()

A default constructor. Uses the default value of lambda=0.15.

Hiemstra_LM

public Hiemstra_LM(double lambda)

Constructs an instance of this class with the specified value for the parameter lambda.

Parameters:

lambda - the smoothing parameter.

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 Hiemestra_LM 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 n_t,
                          double F_t,
                          double keyFrequency)

Uses Hiemstra_LM 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

n_t - The document frequency of the term

F_t - the term frequency in the collection

keyFrequency - the term frequency in the query

Returns:

the score assigned by the weighting model Hiemstra_LM.