Package org.apache.lucene.search.similarities

Class IBSimilarity

java.lang.Object

org.apache.lucene.search.similarities.Similarity

org.apache.lucene.search.similarities.SimilarityBase

org.apache.lucene.search.similarities.IBSimilarity

public class IBSimilarity
extends SimilarityBase

Provides a framework for the family of information-based models, as described in Stéphane Clinchant and Eric Gaussier. 2010. Information-based models for ad hoc IR. In Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval (SIGIR '10). ACM, New York, NY, USA, 234-241.

The retrieval function is of the form RSV(q, d) = ∑ -x^q_w log Prob(X_w ≥ t^d_w | λ_w), where

• x^q_w is the query boost;
• X_w is a random variable that counts the occurrences of word w;
• t^d_w is the normalized term frequency;
• λ_w is a parameter.

The framework described in the paper has many similarities to the DFR framework (see DFRSimilarity). It is possible that the two Similarities will be merged at one point.

To construct an IBSimilarity, you must specify the implementations for all three components of the Information-Based model.

1. Distribution: Probabilistic distribution used to model term occurrence
   • DistributionLL: Log-logistic
   • DistributionLL: Smoothed power-law
2. Lambda: λ_w parameter of the probability distribution
   • LambdaDF: Nw/N or average number of documents where w occurs
   • LambdaTTF: Fw/N or average number of occurrences of w in the collection
3. Normalization: Term frequency normalization

   Any supported DFR normalization (listed in DFRSimilarity)

See Also:

• DFRSimilarity

Nested Class Summary

Nested classes/interfaces inherited from class org.apache.lucene.search.similarities.Similarity

Similarity.SimScorer, Similarity.SimWeight

Constructor Summary

Constructors

Constructor	Description
IBSimilarity(Distribution distribution, Lambda lambda, Normalization normalization)	Creates IBSimilarity from the three components.

Method Summary

Modifier and Type	Method	Description
Distribution	getDistribution()	Returns the distribution
Lambda	getLambda()	Returns the distribution's lambda parameter
Normalization	getNormalization()	Returns the term frequency normalization
String	toString()	The name of IB methods follow the pattern IB <distribution> <lambda><normalization>.

Methods inherited from class org.apache.lucene.search.similarities.SimilarityBase

computeNorm, computeWeight, getDiscountOverlaps, log2, setDiscountOverlaps, simScorer

Methods inherited from class org.apache.lucene.search.similarities.Similarity

coord, queryNorm

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Details

IBSimilarity

public IBSimilarity(Distribution distribution,
 Lambda lambda,
 Normalization normalization)

Creates IBSimilarity from the three components.

Note that null values are not allowed: if you want no normalization, instead pass Normalization.NoNormalization.

Parameters:

distribution - probabilistic distribution modeling term occurrence

lambda - distribution's λ_w parameter

normalization - term frequency normalization

Method Details

toString

public String toString()

The name of IB methods follow the pattern IB <distribution> <lambda><normalization>. The name of the distribution is the same as in the original paper; for the names of lambda parameters, refer to the javadoc of the Lambda classes.

Specified by:

toString in class SimilarityBase

getDistribution

public Distribution getDistribution()

Returns the distribution

getLambda

public Lambda getLambda()

Returns the distribution's lambda parameter

getNormalization

public Normalization getNormalization()

Returns the term frequency normalization