org.terrier.matching.models

Class DLH

java.lang.Object

org.terrier.matching.models.WeightingModel

org.terrier.matching.models.DLH

All Implemented Interfaces:

Serializable, Cloneable, Model

public class DLH
extends WeightingModel

This class implements the DLH weighting model. This is a parameter-free weighting model. Even if the user specifies a parameter value, it will NOT affect the results. It is highly recomended to use the model with query expansion.

References

1. Frequentist and Bayesian approach to Information Retrieval. G. Amati. In Proceedings of the 28th European Conference on IR Research (ECIR 2006). LNCS vol 3936, pages 13--24.

Author:

Gianni Amati, Ben He, 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
DLH() A default constructor.

Method Summary

Modifier and Type	Method and Description
String	getInfo() Returns the name of the model.
double	score(double tf, double docLength) Uses DLH to compute a weight for a term in a document.

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

DLH

public DLH()

A default constructor.

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 DLH 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