org.terrier.matching.models
Class XSqrA_M

java.lang.Object
  org.terrier.matching.models.WeightingModel
      org.terrier.matching.models.XSqrA_M

All Implemented Interfaces:

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

public class XSqrA_M
extends WeightingModel

This class implements the XSqrA_M weighting model, which computed the inner product of Pearson's X^2 with the information growth computed with the multinomial M. It is an unsupervised DFR model of IR (free from parameters), which can be used on short or medium verbose queries.

XSqrA_M has a high performance, and in particular has statistically significant better MAP performance than all other supervised models on the GOV2 collection. MAP for short (title only) and medium (title+description) topics, and comparative p values (two-tailed paired t-test) compared to supervised models (with optimal MAP parameter values) are as follows:

Queries	MAP of XSqrA_M	LGD	Dirichlet_LM	PL2	BM25	In_expB2
short	0.3156	p=0.3277	p=0.0075	p=0.0055	p=0.0064	p=0.0002
medium	0.3311	p=2.3E-07	p=0.0002	p=0.0395	p=0.0025	p=2.4E-10

References 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.

Since:

3.5

Author:

Gianni Amati

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

XSqrA_M()
A default constructor to make this model.

Method Summary

java.lang.String	getInfo() Returns the name of the model, in this case "XSqrA_M"
double	score(double tf, double docLength) Uses XSqrA_M to compute a weight for a term in a document.
double	score(double tf, double docLength, double documentFrequency, double termFrequency, double keyFrequency) Uses XSqrA_M 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

XSqrA_M

public XSqrA_M()

A default constructor to make this model.

Method Detail

getInfo

public final java.lang.String getInfo()

Returns the name of the model, in this case "XSqrA_M"

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 XSqrA_M to compute a weight for a term in a document.

Specified by:

score in class WeightingModel

Parameters:

tf - The term frequency of the term 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 XSqrA_M to compute a weight for a term in a document.

Specified by:

score in class WeightingModel

Parameters:

tf - The term frequency of the term in the document

docLength - the document's length

documentFrequency - The document frequency of the term (ignored)

termFrequency - the term frequency in the collection (ignored)

keyFrequency - the term frequency in the query (ignored).

Returns:

the score assigned by the weighting model XSqrA_M.