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
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.
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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
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Field Summary
Fields inherited from class org.apache.lucene.search.similarities.LMSimilarity
collectionModel
Fields inherited from class org.apache.lucene.search.similarities.SimilarityBase
discountOverlaps
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Constructor Summary
ConstructorDescriptionInstantiates 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 TypeMethodDescriptionprotected void
explain
(List<Explanation> subs, BasicStats stats, double freq, double docLen) Subclasses should implement this method to explain the score.protected Explanation
explain
(BasicStats stats, Explanation freq, double docLen) Explains the score.float
getMu()
Returns the μ parameter.getName()
Returns the name of the LM method.protected double
score
(BasicStats stats, double freq, double docLen) Scores the documentdoc
.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
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Constructor Details
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LMDirichletSimilarity
Instantiates the similarity with the provided μ parameter. -
LMDirichletSimilarity
public LMDirichletSimilarity(float mu) Instantiates the similarity with the provided μ parameter. -
LMDirichletSimilarity
Instantiates the similarity with the default μ value of 2000. -
LMDirichletSimilarity
public LMDirichletSimilarity()Instantiates the similarity with the default μ value of 2000.
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Method Details
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score
Description copied from class:SimilarityBase
Scores the documentdoc
.Subclasses must apply their scoring formula in this class.
- Specified by:
score
in classSimilarityBase
- Parameters:
stats
- the corpus level statistics.freq
- the term frequency.docLen
- the document length.- Returns:
- the score.
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explain
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 classLMSimilarity
- Parameters:
subs
- the list of details of the explanation to extendstats
- the corpus level statistics.freq
- the term frequency.docLen
- the document length.
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explain
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 theSimilarityBase.score(BasicStats, double, double)
method) and the explanation for the term frequency. Subclasses content with this format may add additional details inSimilarityBase.explain(List, BasicStats, double, double)
.- Overrides:
explain
in classSimilarityBase
- Parameters:
stats
- the corpus level statistics.freq
- the term frequency and its explanation.docLen
- the document length.- Returns:
- the explanation.
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getMu
public float getMu()Returns the μ parameter. -
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 classLMSimilarity
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