Package  Description 

org.apache.lucene.search.similarities 
This package contains the various ranking models that can be used in Lucene.

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
F2EXP 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) = (docLenqueryLen)*queryLen*s/avdl

class 
AxiomaticF3LOG
F2EXP 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) = (docLenqueryLen)*queryLen*s/avdl

class 
DFISimilarity
Implements the Divergence from Independence (DFI) model based on Chisquare statistics
(i.e., standardized Chisquared 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 informationbased models, as described
in Stéphane Clinchant and Eric Gaussier.

class 
LMDirichletSimilarity
Bayesian smoothing using Dirichlet priors.

class 
LMJelinekMercerSimilarity
Language model based on the JelinekMercer smoothing method.

class 
LMSimilarity
Abstract superclass for language modeling Similarities.

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