Uses of Class org.apache.lucene.search.similarities.SimilarityBase (Lucene 10.5.1 core API)
Description: use: package: org.apache.lucene.search.similarities, class: SimilarityBase

# Uses of Class
org.apache.lucene.search.similarities.SimilarityBase

Packages that use SimilarityBase
Package
Description
org.apache.lucene.search.similarities
This package contains the various ranking models that can be used in Lucene.

- ## Uses of SimilarityBase in org.apache.lucene.search.similarities

  Subclasses of SimilarityBase 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`
  `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.