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

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.

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 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.

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 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	IndriDirichletSimilarity	Bayesian smoothing using Dirichlet priors as implemented in the Indri Search engine (http://www.lemurproject.org/indri.php).
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
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.