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Terrier IR Platform 1.1.1 |
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java.lang.Objectuk.ac.gla.terrier.matching.models.languagemodel.LanguageModel
uk.ac.gla.terrier.matching.models.languagemodel.PonteCroft
public class PonteCroft
This class implements Ponte & Croft's language modelling approach.
| Constructor Summary | |
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PonteCroft()
The default constructor. |
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| Method Summary | |
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double |
averageTermGenerationProbability(int[] tf,
double[] docLength)
The method computes the average term generation probability of a term in vocabulary. |
java.lang.String |
getInfo()
Returns the name of the model. |
double |
risk(double tf,
double docLength,
double termEstimate)
The method computes the risk of retrieving a seen query term. |
double |
scoreSeenNonQuery(double tf,
double docLength,
double termFrequency,
double termEstimate)
The method assigns score for a seen non-query term. |
double |
scoreSeenQuery(double tf,
double docLength,
double termFrequency,
double termEstimate)
The method assigns score for a seen query term. |
double |
scoreUnseenNonQuery(double termFrequency)
The method assigns score for a unseen non-query term. |
double |
scoreUnseenQuery(double termFrequency)
The method assigns score for a unseen query term. |
void |
setAverageDocumentLength(double a)
Set the average document length in the collection. |
void |
setNumberOfPointers(double n)
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void |
setNumberOfTokens(double value)
Set the number of tokens in the whole collection. |
void |
setNumberOfUniqueTerms(double n)
Set the number of unique terms in the collection. |
| Methods inherited from class uk.ac.gla.terrier.matching.models.languagemodel.LanguageModel |
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getParameter, setNumberOfDocuments, setParameter, setTermFrequency |
| Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
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public PonteCroft()
| Method Detail |
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public java.lang.String getInfo()
getInfo in interface ModelgetInfo in class LanguageModel
public double scoreSeenQuery(double tf,
double docLength,
double termFrequency,
double termEstimate)
scoreSeenQuery in class LanguageModeltf - The within-document frequency.docLength - The length of the weighted document.termFrequency - The term frequency in the collection.termEstimate - The term estimate of the query term.
public double scoreSeenNonQuery(double tf,
double docLength,
double termFrequency,
double termEstimate)
scoreSeenNonQuery in class LanguageModeltf - The within-document frequency.docLength - The length of the weighted document.termFrequency - The term frequency in the collection.termEstimate - The term estimate of the query term.
public double scoreUnseenQuery(double termFrequency)
scoreUnseenQuery in class LanguageModeltermFrequency - The term frequency in the collection.
public double scoreUnseenNonQuery(double termFrequency)
scoreUnseenNonQuery in class LanguageModeltermFrequency - The term frequency in the collection.
public double risk(double tf,
double docLength,
double termEstimate)
risk in class LanguageModeltf - The within-document frequency.docLength - The length of the weighted document.termEstimate - The term estimate of the query term.
public double averageTermGenerationProbability(int[] tf,
double[] docLength)
averageTermGenerationProbability in class LanguageModeltf - An array of within-document frequency of a query term in all
documents where it occurs.docLength - The length of all the documents where the term occurs.
public void setNumberOfTokens(double value)
Model
value - The number of tokens in the whole collection.public void setAverageDocumentLength(double a)
Model
a - The average document length in the collection.public void setNumberOfUniqueTerms(double n)
Model
n - double The number of unique terms in the collection.public void setNumberOfPointers(double n)
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Terrier IR Platform 1.1.1 |
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