public class

SimilarityDelegator

extends Similarity
java.lang.Object
   ↳ org.apache.lucene.search.Similarity
     ↳ org.apache.lucene.search.SimilarityDelegator

Class Overview

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

Summary

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Inherited Constants
From class org.apache.lucene.search.Similarity
Public Constructors
SimilarityDelegator(Similarity delegee)
Construct a Similarity that delegates all methods to another.
Public Methods
float computeNorm(String fieldName, FieldInvertState state)
Compute the normalization value for a field, given the accumulated state of term processing for this field (see FieldInvertState).
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 scorePayload(int docId, String fieldName, int start, int end, byte[] payload, int offset, int length)
Calculate a scoring factor based on the data in the payload.
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.
[Expand]
Inherited Methods
From class org.apache.lucene.search.Similarity
From class java.lang.Object

Public Constructors

public SimilarityDelegator (Similarity delegee)

Construct a Similarity that delegates all methods to another.

Parameters
delegee the Similarity implementation to delegate to

Public Methods

public float computeNorm (String fieldName, FieldInvertState state)

Compute the normalization value for a field, given the accumulated state of term processing for this field (see FieldInvertState).

Implementations should calculate a float value based on the field state and then return that value.

For backward compatibility this method by default calls lengthNorm(String, int) passing getLength() as the second argument, and then multiplies this value by getBoost().

WARNING: This API is new and experimental and may suddenly change.

Parameters
fieldName field name
state current processing state for this field
Returns
  • the calculated float norm

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.

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

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 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.

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

public float lengthNorm (String fieldName, int numTerms)

Computes the normalization value for a field given the total number of terms contained in a field. These values, together with field boosts, are stored in an index and multipled into scores for hits on each field by the search code.

Matches in longer fields are less precise, so implementations of this method usually return smaller values when numTokens is large, and larger values when numTokens is small.

Note that the return values are computed under addDocument(org.apache.lucene.document.Document) and then stored using encodeNorm(float). Thus they have limited precision, and documents must be re-indexed if this method is altered.

Parameters
fieldName the name of the field
numTerms the total number of tokens contained in fields named fieldName of doc.
Returns
  • a normalization factor for hits on this field of this document

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 multiplied into the weight of each query term. While the classic query normalization factor is computed as 1/sqrt(sumOfSquaredWeights), other implementations might completely ignore sumOfSquaredWeights (ie return 1).

This does not affect ranking, but the default implementation does make scores from different queries more comparable than they would be by eliminating the magnitude of the Query vector as a factor in the score.

Parameters
sumOfSquaredWeights the sum of the squares of query term weights
Returns
  • a normalization factor for query weights

public float scorePayload (int docId, String fieldName, int start, int end, byte[] payload, int offset, int length)

Calculate a scoring factor based on the data in the payload. Overriding implementations are responsible for interpreting what is in the payload. Lucene makes no assumptions about what is in the byte array.

The default implementation returns 1.

Parameters
docId The docId currently being scored. If this value is NO_DOC_ID_PROVIDED, then it should be assumed that the PayloadQuery implementation does not provide document information
fieldName The fieldName of the term this payload belongs to
start The start position of the payload
end The end position of the payload
payload The payload byte array to be scored
offset The offset into the payload array
length The length in the array
Returns
  • An implementation dependent float to be used as a scoring factor

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 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.

Parameters
distance the edit distance of this sloppy phrase match
Returns
  • the frequency increment for this match

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 idf(int, int) 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.

Parameters
freq the frequency of a term within a document
Returns
  • a score factor based on a term's within-document frequency