org.apache.lucene.search

Class SimilarityDelegator

Implemented Interfaces:
Serializable

public class SimilarityDelegator
extends Similarity

Expert: Delegating scoring implementation. Useful in Query.getSimilarity(Searcher) implementations, to override only certain methods of a Searcher's Similiarty implementation..

Constructor Summary

SimilarityDelegator(Similarity delegee)
Construct a Similarity that delegates all methods to another.

Method Summary

float
coord(int overlap, int maxOverlap)
Computes a score factor based on the fraction of all query terms that a document contains.
float
idf(int docFreq, int numDocs)
Computes a score factor based on a term's document frequency (the number of documents which contain the term).
float
lengthNorm(String fieldName, int numTerms)
Computes the normalization value for a field given the total number of terms contained in a field.
float
queryNorm(float sumOfSquaredWeights)
Computes the normalization value for a query given the sum of the squared weights of each of the query terms.
float
sloppyFreq(int distance)
Computes the amount of a sloppy phrase match, based on an edit distance.
float
tf(float freq)
Computes a score factor based on a term or phrase's frequency in a document.

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

coord, decodeNorm, encodeNorm, getDefault, getNormDecoder, idf, idf, idf, lengthNorm, queryNorm, setDefault, sloppyFreq, tf, tf

Constructor Details

SimilarityDelegator

public SimilarityDelegator(Similarity delegee)
Construct a Similarity that delegates all methods to another.
Parameters:
delegee - the Similarity implementation to delegate to

Method Details

coord

public float coord(int overlap,
                   int maxOverlap)
Computes a score factor based on the fraction of all query terms that a document contains. This value is multiplied into scores.

The presence of a large portion of the query terms indicates a better match with the query, so implementations of this method usually return larger values when the ratio between these parameters is large and smaller values when the ratio between them is small.

Overrides:
coord in interface Similarity
Parameters:
overlap - the number of query terms matched in the document
maxOverlap - the total number of terms in the query
Returns:
a score factor based on term overlap with the query

idf

public float idf(int docFreq,
                 int numDocs)
Computes a score factor based on a term's document frequency (the number of documents which contain the term). This value is multiplied by the Similarity.tf(int) factor for each term in the query and these products are then summed to form the initial score for a document.

Terms that occur in fewer documents are better indicators of topic, so implementations of this method usually return larger values for rare terms, and smaller values for common terms.

Overrides:
idf in interface Similarity
Parameters:
docFreq - the number of documents which contain the term
numDocs - the total number of documents in the collection
Returns:
a score factor based on the term's document frequency

lengthNorm

public float lengthNorm(String fieldName,
                        int numTerms)
Overrides:
lengthNorm in interface Similarity
Parameters:
fieldName - the name of the field
Returns:
a normalization factor for hits on this field of this document

queryNorm

public float queryNorm(float sumOfSquaredWeights)
Computes the normalization value for a query given the sum of the squared weights of each of the query terms. This value is then multipled into the weight of each query term.

This does not affect ranking, but rather just attempts to make scores from different queries comparable.

Overrides:
queryNorm in interface Similarity
Parameters:
sumOfSquaredWeights - the sum of the squares of query term weights
Returns:
a normalization factor for query weights

sloppyFreq

public float sloppyFreq(int distance)
Computes the amount of a sloppy phrase match, based on an edit distance. This value is summed for each sloppy phrase match in a document to form the frequency that is passed to Similarity.tf(float).

A phrase match with a small edit distance to a document passage more closely matches the document, so implementations of this method usually return larger values when the edit distance is small and smaller values when it is large.

Overrides:
sloppyFreq in interface Similarity
Parameters:
distance - the edit distance of this sloppy phrase match
Returns:
the frequency increment for this match

tf

public float tf(float freq)
Computes a score factor based on a term or phrase's frequency in a document. This value is multiplied by the Similarity.idf(Term,Searcher) factor for each term in the query and these products are then summed to form the initial score for a document.

Terms and phrases repeated in a document indicate the topic of the document, so implementations of this method usually return larger values when freq is large, and smaller values when freq is small.

Overrides:
tf in interface Similarity
Parameters:
freq - the frequency of a term within a document
Returns:
a score factor based on a term's within-document frequency

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