Uses of Class
org.apache.lucene.search.similarities.Similarity
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Packages that use Similarity Package Description org.apache.lucene.index Code to maintain and access indices.org.apache.lucene.search Code to search indices.org.apache.lucene.search.similarities This package contains the various ranking models that can be used in Lucene.org.apache.lucene.search.spans The calculus of spans. -
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Uses of Similarity in org.apache.lucene.index
Fields in org.apache.lucene.index declared as Similarity Modifier and Type Field Description protected Similarity
LiveIndexWriterConfig. similarity
Similarity
to use when encoding norms.Methods in org.apache.lucene.index that return Similarity Modifier and Type Method Description Similarity
IndexWriterConfig. getSimilarity()
Similarity
LiveIndexWriterConfig. getSimilarity()
Expert: returns theSimilarity
implementation used by thisIndexWriter
.Methods in org.apache.lucene.index with parameters of type Similarity Modifier and Type Method Description IndexWriterConfig
IndexWriterConfig. setSimilarity(Similarity similarity)
Expert: set theSimilarity
implementation used by this IndexWriter. -
Uses of Similarity in org.apache.lucene.search
Methods in org.apache.lucene.search that return Similarity Modifier and Type Method Description static Similarity
IndexSearcher. getDefaultSimilarity()
Expert: returns a default Similarity instance.Similarity
IndexSearcher. getSimilarity()
Expert: Get theSimilarity
to use to compute scores.Methods in org.apache.lucene.search with parameters of type Similarity Modifier and Type Method Description void
IndexSearcher. setSimilarity(Similarity similarity)
Expert: Set the Similarity implementation used by this IndexSearcher. -
Uses of Similarity in org.apache.lucene.search.similarities
Subclasses of Similarity in org.apache.lucene.search.similarities Modifier and Type Class Description class
Axiomatic
Axiomatic approaches for IR.class
AxiomaticF1EXP
F1EXP is defined as Sum(tf(term_doc_freq)*ln(docLen)*IDF(term)) where IDF(t) = pow((N+1)/df(t), k) N=total num of docs, df=doc freqclass
AxiomaticF1LOG
F1LOG is defined as Sum(tf(term_doc_freq)*ln(docLen)*IDF(term)) where IDF(t) = ln((N+1)/df(t)) N=total num of docs, df=doc freqclass
AxiomaticF2EXP
F2EXP is defined as Sum(tfln(term_doc_freq, docLen)*IDF(term)) where IDF(t) = pow((N+1)/df(t), k) N=total num of docs, df=doc freqclass
AxiomaticF2LOG
F2EXP is defined as Sum(tfln(term_doc_freq, docLen)*IDF(term)) where IDF(t) = ln((N+1)/df(t)) N=total num of docs, df=doc freqclass
AxiomaticF3EXP
F3EXP is defined as Sum(tf(term_doc_freq)*IDF(term)-gamma(docLen, queryLen)) where IDF(t) = pow((N+1)/df(t), k) N=total num of docs, df=doc freq gamma(docLen, queryLen) = (docLen-queryLen)*queryLen*s/avdl NOTE: the gamma function of this similarity creates negative scoresclass
AxiomaticF3LOG
F3EXP is defined as Sum(tf(term_doc_freq)*IDF(term)-gamma(docLen, queryLen)) where IDF(t) = ln((N+1)/df(t)) N=total num of docs, df=doc freq gamma(docLen, queryLen) = (docLen-queryLen)*queryLen*s/avdl NOTE: the gamma function of this similarity creates negative scoresclass
BM25Similarity
BM25 Similarity.class
BooleanSimilarity
Simple similarity that gives terms a score that is equal to their query boost.class
ClassicSimilarity
Expert: Historical scoring implementation.class
DFISimilarity
Implements the Divergence from Independence (DFI) model based on Chi-square statistics (i.e., standardized Chi-squared distance from independence in term frequency tf).class
DFRSimilarity
Implements the divergence from randomness (DFR) framework introduced in Gianni Amati and Cornelis Joost Van Rijsbergen.class
IBSimilarity
Provides a framework for the family of information-based models, as described in Stéphane Clinchant and Eric Gaussier.class
LMDirichletSimilarity
Bayesian smoothing using Dirichlet priors.class
LMJelinekMercerSimilarity
Language model based on the Jelinek-Mercer smoothing method.class
LMSimilarity
Abstract superclass for language modeling Similarities.class
MultiSimilarity
Implements the CombSUM method for combining evidence from multiple similarity values described in: Joseph A.class
PerFieldSimilarityWrapper
Provides the ability to use a differentSimilarity
for different fields.class
SimilarityBase
A subclass ofSimilarity
that provides a simplified API for its descendants.class
TFIDFSimilarity
Implementation ofSimilarity
with the Vector Space Model.Fields in org.apache.lucene.search.similarities declared as Similarity Modifier and Type Field Description protected Similarity[]
MultiSimilarity. sims
the sub-similarities used to create the combined scoreMethods in org.apache.lucene.search.similarities that return Similarity Modifier and Type Method Description abstract Similarity
PerFieldSimilarityWrapper. get(String name)
Returns aSimilarity
for scoring a field.Constructors in org.apache.lucene.search.similarities with parameters of type Similarity Constructor Description MultiSimilarity(Similarity[] sims)
Creates a MultiSimilarity which will sum the scores of the providedsims
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Uses of Similarity in org.apache.lucene.search.spans
Fields in org.apache.lucene.search.spans declared as Similarity Modifier and Type Field Description protected Similarity
SpanWeight. similarity
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