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.
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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, Similarity.SimWeight
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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
ConstructorsConstructorDescriptionInstantiates 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
(Explanation expl, BasicStats stats, int doc, float freq, float docLen) Subclasses should implement this method to explain the score.float
getMu()
Returns the μ parameter.getName()
Returns the name of the LM method.protected float
score
(BasicStats stats, float freq, float 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, computeWeight, decodeNormValue, encodeNormValue, explain, getDiscountOverlaps, log2, setDiscountOverlaps, simScorer
Methods inherited from class org.apache.lucene.search.similarities.Similarity
coord, queryNorm
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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:
expl
- the explanation to extend with details.stats
- the corpus level statistics.doc
- the document id.freq
- the term frequency.docLen
- the document length.
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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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