org.terrier.matching.models.basicmodel
Class IF

java.lang.Object
  org.terrier.matching.models.basicmodel.BasicModel
      org.terrier.matching.models.basicmodel.IF

All Implemented Interfaces:

java.io.Serializable

public class IF
extends BasicModel

This class implements the IF basic model for randomness.

Author:

Ben He

See Also:

Serialized Form

Field Summary

protected java.lang.String

modelName The name of the model.

Fields inherited from class org.terrier.matching.models.basicmodel.BasicModel

i, numberOfDocuments, numberOfTokens

Constructor Summary

IF()
A default constructor.

Method Summary

java.lang.String	getInfo() Returns the name of the model.
double	score(double tf, double documentFrequency, double termFrequency, double keyFrequency, double documentLength) This method computes the score for the implemented weighting model.

Methods inherited from class org.terrier.matching.models.basicmodel.BasicModel

setNumberOfDocuments, setNumberOfTokens, stirlingPower

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

modelName

protected java.lang.String modelName

The name of the model.

Constructor Detail

IF

public IF()

A default constructor.

Method Detail

getInfo

public java.lang.String getInfo()

Returns the name of the model.

Specified by:

getInfo in class BasicModel

Returns:

the name of the model

score

public double score(double tf,
                    double documentFrequency,
                    double termFrequency,
                    double keyFrequency,
                    double documentLength)

This method computes the score for the implemented weighting model.

Specified by:

score in class BasicModel

Parameters:

tf - The term frequency in the document

documentFrequency - The document frequency of the term

termFrequency - the term frequency in the collection

keyFrequency - The normalised query term frequency.

documentLength - The length of the document.

Returns:

the score returned by the implemented weighting model.