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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
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.
Nested Class Summary |
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Nested classes/interfaces inherited from class org.apache.lucene.search.similarities.LMSimilarity |
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LMSimilarity.CollectionModel, LMSimilarity.DefaultCollectionModel, LMSimilarity.LMStats |
Nested classes/interfaces inherited from class org.apache.lucene.search.similarities.Similarity |
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Similarity.SimScorer, Similarity.SimWeight |
Field Summary |
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Fields inherited from class org.apache.lucene.search.similarities.LMSimilarity |
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collectionModel |
Fields inherited from class org.apache.lucene.search.similarities.SimilarityBase |
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discountOverlaps |
Constructor Summary | |
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LMDirichletSimilarity()
Instantiates the similarity with the default μ value of 2000. |
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LMDirichletSimilarity(float mu)
Instantiates the similarity with the provided μ parameter. |
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LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel)
Instantiates the similarity with the default μ value of 2000. |
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LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel,
float mu)
Instantiates the similarity with the provided μ parameter. |
Method Summary | |
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protected 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. |
String |
getName()
Returns the name of the LM method. |
protected float |
score(BasicStats stats,
float freq,
float docLen)
Scores the document doc . |
Methods inherited from class org.apache.lucene.search.similarities.LMSimilarity |
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fillBasicStats, newStats, toString |
Methods inherited from class org.apache.lucene.search.similarities.SimilarityBase |
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computeNorm, computeWeight, decodeNormValue, encodeNormValue, explain, getDiscountOverlaps, log2, setDiscountOverlaps, simScorer |
Methods inherited from class org.apache.lucene.search.similarities.Similarity |
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coord, queryNorm |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel, float mu)
public LMDirichletSimilarity(float mu)
public LMDirichletSimilarity(LMSimilarity.CollectionModel collectionModel)
public LMDirichletSimilarity()
Method Detail |
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protected float score(BasicStats stats, float freq, float docLen)
SimilarityBase
doc
.
Subclasses must apply their scoring formula in this class.
score
in class SimilarityBase
stats
- the corpus level statistics.freq
- the term frequency.docLen
- the document length.
protected void explain(Explanation expl, BasicStats stats, int doc, float freq, float docLen)
SimilarityBase
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.
explain
in class LMSimilarity
expl
- the explanation to extend with details.stats
- the corpus level statistics.doc
- the document id.freq
- the term frequency.docLen
- the document length.public float getMu()
public String getName()
LMSimilarity
Used in LMSimilarity.toString()
getName
in class LMSimilarity
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