org.apache.lucene.search.similarities

Class LMDirichletSimilarity

java.lang.Object

org.apache.lucene.search.similarities.Similarity

org.apache.lucene.search.similarities.SimilarityBase

org.apache.lucene.search.similarities.LMSimilarity

org.apache.lucene.search.similarities.LMDirichletSimilarity

public class LMDirichletSimilarity
extends LMSimilarity

Bayesian smoothing using Dirichlet priors. From Chengxiang Zhai and John Lafferty. 2001. A study of smoothing methods for language models applied to Ad Hoc information retrieval. In Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '01). ACM, New York, NY, USA, 334-342.

The formula as defined the paper assigns a negative score to documents that contain the term, but with fewer occurrences than predicted by the collection language model. The Lucene implementation returns 0 for such documents.

WARNING: This API is experimental and might change in incompatible ways in the next release.

Nested Class Summary

Nested classes/interfaces inherited from class org.apache.lucene.search.similarities.LMSimilarity

LMSimilarity.CollectionModel, LMSimilarity.DefaultCollectionModel, LMSimilarity.LMStats

Nested classes/interfaces inherited from class org.apache.lucene.search.similarities.Similarity

Similarity.SimScorer

Field Summary

Fields inherited from class org.apache.lucene.search.similarities.LMSimilarity

collectionModel

Fields inherited from class org.apache.lucene.search.similarities.SimilarityBase

discountOverlaps

Constructor Summary

Constructors

Constructor and Description
LMDirichletSimilarity() Instantiates the similarity with the default μ value of 2000.
LMDirichletSimilarity(float mu) Instantiates the similarity with the provided μ parameter.
LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel) Instantiates the similarity with the default μ value of 2000.
LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel, float mu) Instantiates the similarity with the provided μ parameter.

Method Summary

Modifier and Type	Method and Description
protected Explanation	explain(BasicStats stats, Explanation freq, double docLen) Explains the score.
protected void	explain(List<Explanation> subs, BasicStats stats, double freq, double docLen) Subclasses should implement this method to explain the score.
float	getMu() Returns the μ parameter.
String	getName() Returns the name of the LM method.
protected double	score(BasicStats stats, double freq, double docLen) Scores the document doc.

Methods inherited from class org.apache.lucene.search.similarities.LMSimilarity

fillBasicStats, newStats, toString

Methods inherited from class org.apache.lucene.search.similarities.SimilarityBase

computeNorm, getDiscountOverlaps, log2, scorer, setDiscountOverlaps

Methods inherited from class java.lang.Object

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

Constructor Detail

LMDirichletSimilarity

public LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel,
                             float mu)

Instantiates the similarity with the provided μ parameter.

LMDirichletSimilarity

public LMDirichletSimilarity(float mu)

Instantiates the similarity with the provided μ parameter.

LMDirichletSimilarity

public LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel)

Instantiates the similarity with the default μ value of 2000.

LMDirichletSimilarity

public LMDirichletSimilarity()

Instantiates the similarity with the default μ value of 2000.

Method Detail

score

protected double score(BasicStats stats,
                       double freq,
                       double docLen)

Description copied from class: SimilarityBase

Scores the document doc.

Subclasses must apply their scoring formula in this class.

Specified by:

score in class SimilarityBase

Parameters:

stats - the corpus level statistics.

freq - the term frequency.

docLen - the document length.

Returns:

the score.

explain

protected void explain(List<Explanation> subs,
                       BasicStats stats,
                       double freq,
                       double docLen)

Description copied from class: SimilarityBase

Subclasses should implement this method to explain the score. expl already contains the score, the name of the class and the doc id, as well as the term frequency and its explanation; subclasses can add additional clauses to explain details of their scoring formulae.

The default implementation does nothing.

Overrides:

explain in class LMSimilarity

Parameters:

subs - the list of details of the explanation to extend

stats - the corpus level statistics.

freq - the term frequency.

docLen - the document length.

explain

protected Explanation explain(BasicStats stats,
                              Explanation freq,
                              double docLen)

Description copied from class: SimilarityBase

Explains the score. The implementation here provides a basic explanation in the format score(name-of-similarity, doc=doc-id, freq=term-frequency), computed from:, and attaches the score (computed via the SimilarityBase.score(BasicStats, double, double) method) and the explanation for the term frequency. Subclasses content with this format may add additional details in SimilarityBase.explain(List, BasicStats, double, double).

Overrides:

explain in class SimilarityBase

Parameters:

stats - the corpus level statistics.

freq - the term frequency and its explanation.

docLen - the document length.

Returns:

the explanation.

getMu

public float getMu()

Returns the μ parameter.

getName

public String getName()

Description copied from class: LMSimilarity

Returns the name of the LM method. The values of the parameters should be included as well.

Used in LMSimilarity.toString()

.

Specified by:

getName in class LMSimilarity