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.
org.apache.lucene.search.spans	The calculus of spans.

Uses of Similarity in org.apache.lucene.index

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

Modifier and Type	Field and Description
protected Similarity	LiveIndexWriterConfig.similarity Similarity to use when encoding norms.

Methods in org.apache.lucene.index that return Similarity

Modifier and Type	Method and Description
Similarity	LiveIndexWriterConfig.getSimilarity() Expert: returns the Similarity implementation used by this IndexWriter.
Similarity	IndexWriterConfig.getSimilarity()

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

Modifier and Type	Method and 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 and 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 and 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 and 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 and Description
protected 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 and 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

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

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

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

Modifier and Type	Field and Description
protected Similarity	SpanWeight.similarity