Class LMDirichletSimilarity
- java.lang.Object
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- org.apache.lucene.search.similarities.Similarity
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- org.apache.lucene.search.similarities.SimilarityBase
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- org.apache.lucene.search.similarities.LMSimilarity
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- org.apache.lucene.search.similarities.LMDirichletSimilarity
 
 
 
 
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 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 0for 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.LMSimilarityLMSimilarity.CollectionModel, LMSimilarity.DefaultCollectionModel, LMSimilarity.LMStats
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Nested classes/interfaces inherited from class org.apache.lucene.search.similarities.SimilaritySimilarity.SimScorer
 
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Field Summary- 
Fields inherited from class org.apache.lucene.search.similarities.LMSimilaritycollectionModel
 
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Constructor SummaryConstructors Constructor 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, boolean discountOverlaps, float mu)Instantiates the similarity with the provided parameters.LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel, float mu)Instantiates the similarity with the provided μ parameter.
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Method SummaryAll Methods Instance Methods Concrete Methods Modifier and Type Method Description protected voidexplain(List<Explanation> subs, BasicStats stats, double freq, double docLen)Subclasses should implement this method to explain the score.protected Explanationexplain(BasicStats stats, Explanation freq, double docLen)Explains the score.floatgetMu()Returns the μ parameter.StringgetName()Returns the name of the LM method.protected doublescore(BasicStats stats, double freq, double docLen)Scores the documentdoc.- 
Methods inherited from class org.apache.lucene.search.similarities.LMSimilarityfillBasicStats, newStats, toString
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Methods inherited from class org.apache.lucene.search.similarities.SimilarityBaselog2, scorer
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Methods inherited from class org.apache.lucene.search.similarities.SimilaritycomputeNorm, getDiscountOverlaps
 
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Constructor Detail- 
LMDirichletSimilaritypublic LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel, float mu) Instantiates the similarity with the provided μ parameter.
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LMDirichletSimilaritypublic LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel, boolean discountOverlaps, float mu) Instantiates the similarity with the provided parameters.
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LMDirichletSimilaritypublic LMDirichletSimilarity(float mu) Instantiates the similarity with the provided μ parameter.
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LMDirichletSimilaritypublic LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel) Instantiates the similarity with the default μ value of 2000.
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LMDirichletSimilaritypublic LMDirichletSimilarity() Instantiates the similarity with the default μ value of 2000.
 
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Method Detail- 
scoreprotected double score(BasicStats stats, double freq, double docLen) Description copied from class:SimilarityBaseScores the documentdoc.Subclasses must apply their scoring formula in this class. - Specified by:
- scorein class- SimilarityBase
- Parameters:
- stats- the corpus level statistics.
- freq- the term frequency.
- docLen- the document length.
- Returns:
- the score.
 
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explainprotected void explain(List<Explanation> subs, BasicStats stats, double freq, double docLen) Description copied from class:SimilarityBaseSubclasses should implement this method to explain the score.explalready 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:
- explainin 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.
 
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explainprotected Explanation explain(BasicStats stats, Explanation freq, double docLen) Description copied from class:SimilarityBaseExplains 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:
- explainin class- SimilarityBase
- Parameters:
- stats- the corpus level statistics.
- freq- the term frequency and its explanation.
- docLen- the document length.
- Returns:
- the explanation.
 
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getMupublic float getMu() Returns the μ parameter.
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getNamepublic String getName() Description copied from class:LMSimilarityReturns the name of the LM method. The values of the parameters should be included as well.Used in LMSimilarity.toString().- Specified by:
- getNamein class- LMSimilarity
 
 
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