Uses of Class
org.apache.lucene.search.similarities.Similarity

Packages that use Similarity

Package	Description
org.apache.lucene.classification	Uses already seen data (the indexed documents) to classify an input ( can be simple text or a structured document).
org.apache.lucene.classification.document	Uses already seen data (the indexed documents) to classify new documents.
org.apache.lucene.index	Code to maintain and access indices.
org.apache.lucene.index.memory	High-performance single-document main memory Apache Lucene fulltext search index.
org.apache.lucene.misc	Miscellaneous index tools.
org.apache.lucene.monitor	Monitoring framework
org.apache.lucene.queries.function.valuesource	A variety of functions to use with FunctionQuery.
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.similarity	Misc similarity implementations.
org.apache.lucene.search.spans	The calculus of spans.

Uses of Similarity in org.apache.lucene.classification

Constructors in org.apache.lucene.classification with parameters of type Similarity

Modifier	Constructor	Description
	KNearestFuzzyClassifier(IndexReader indexReader, Similarity similarity, Analyzer analyzer, Query query, int k, String classFieldName, String... textFieldNames)	Creates a KNearestFuzzyClassifier.
	KNearestNeighborClassifier(IndexReader indexReader, Similarity similarity, Analyzer analyzer, Query query, int k, int minDocsFreq, int minTermFreq, String classFieldName, String... textFieldNames)	Creates a KNearestNeighborClassifier.

Uses of Similarity in org.apache.lucene.classification.document

Constructors in org.apache.lucene.classification.document with parameters of type Similarity

Modifier	Constructor	Description
	KNearestNeighborDocumentClassifier(IndexReader indexReader, Similarity similarity, Query query, int k, int minDocsFreq, int minTermFreq, String classFieldName, Map<String,Analyzer> field2analyzer, String... textFieldNames)	Creates a KNearestNeighborClassifier.

Uses of Similarity in org.apache.lucene.index

Fields in org.apache.lucene.index declared as Similarity

Modifier and Type	Field	Description
(package private) final Similarity	DefaultIndexingChain.PerField.similarity
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 the Similarity implementation used by this IndexWriter.

Methods in org.apache.lucene.index with parameters of type Similarity

Modifier and Type	Method	Description
IndexWriterConfig	IndexWriterConfig.setSimilarity(Similarity similarity)	Expert: set the Similarity implementation used by this IndexWriter.

Constructors in org.apache.lucene.index with parameters of type Similarity

Modifier	Constructor	Description
(package private)	PerField(int indexCreatedVersionMajor, FieldInfo fieldInfo, boolean invert, Similarity similarity, InfoStream infoStream, Analyzer analyzer)

Uses of Similarity in org.apache.lucene.index.memory

Fields in org.apache.lucene.index.memory declared as Similarity

Modifier and Type	Field	Description
private Similarity	MemoryIndex.normSimilarity

Methods in org.apache.lucene.index.memory with parameters of type Similarity

Modifier and Type	Method	Description
void	MemoryIndex.setSimilarity(Similarity similarity)	Set the Similarity to be used for calculating field norms

Uses of Similarity in org.apache.lucene.misc

Subclasses of Similarity in org.apache.lucene.misc

Modifier and Type	Class	Description
class	SweetSpotSimilarity	A similarity with a lengthNorm that provides for a "plateau" of equally good lengths, and tf helper functions.

Uses of Similarity in org.apache.lucene.monitor

Methods in org.apache.lucene.monitor with parameters of type Similarity

Modifier and Type	Method	Description
static final MatcherFactory<ScoringMatch>	ScoringMatch.matchWithSimilarity(Similarity similarity)

Uses of Similarity in org.apache.lucene.queries.function.valuesource

Methods in org.apache.lucene.queries.function.valuesource with parameters of type Similarity

Modifier and Type	Method	Description
(package private) static TFIDFSimilarity	IDFValueSource.asTFIDF(Similarity sim, String field)

Uses of Similarity in org.apache.lucene.search

Fields in org.apache.lucene.search declared as Similarity

Modifier and Type	Field	Description
private static final Similarity	IndexSearcher.defaultSimilarity
(package private) final Similarity	BooleanWeight.similarity	The Similarity implementation.
private Similarity	IndexSearcher.similarity	The Similarity implementation used by this searcher.
(package private) final Similarity	PhraseWeight.similarity
private final Similarity	SynonymQuery.SynonymWeight.similarity
private final Similarity	TermAutomatonQuery.TermAutomatonWeight.similarity
private final Similarity	TermQuery.TermWeight.similarity

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 the Similarity 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 freq
class	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 freq
class	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 freq
class	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 freq
class	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 scores
class	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 scores
class	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 different Similarity for different fields.
class	SimilarityBase	A subclass of Similarity that provides a simplified API for its descendants.
class	TFIDFSimilarity	Implementation of Similarity with the Vector Space Model.

Fields in org.apache.lucene.search.similarities declared as Similarity

Modifier and Type	Field	Description
private static final Similarity	BooleanSimilarity.BM25_SIM
protected final Similarity[]	MultiSimilarity.sims	the sub-similarities used to create the combined score

Methods in org.apache.lucene.search.similarities that return Similarity

Modifier and Type	Method	Description
abstract Similarity	PerFieldSimilarityWrapper.get(String name)	Returns a Similarity for scoring a field.

Constructors in org.apache.lucene.search.similarities with parameters of type Similarity

Modifier	Constructor	Description
	MultiSimilarity(Similarity[] sims)	Creates a MultiSimilarity which will sum the scores of the provided sims.

Uses of Similarity in org.apache.lucene.search.similarity

Subclasses of Similarity in org.apache.lucene.search.similarity

Modifier and Type	Class	Description
final class	LegacyBM25Similarity	Deprecated. BM25Similarity should be used instead

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 final Similarity	SpanWeight.similarity