Hiemstra_LM (Terrier Information Retrieval Platform 5.5 API)

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

Author:

Jie Peng

See Also:

Serialized Form

Field Summary
- Fields inherited from class org.terrier.matching.models.WeightingModel
  averageDocumentLength, c, cs, documentFrequency, es, i, keyFrequency, numberOfDocuments, numberOfPointers, numberOfPostings, numberOfTokens, numberOfUniqueTerms, rq, termFrequency

Constructor Summary

Constructors
Constructor	Description
`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

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`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.

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
  - 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