org.apache.lucene.search
Class SimilarityDelegator

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

All Implemented Interfaces:

Serializable

Deprecated. this class will be removed in 4.0. Please subclass Similarity or DefaultSimilarity instead.

@Deprecated
public class SimilarityDelegator
extends Similarity

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

See Also:

Serialized Form

Field Summary

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

NO_DOC_ID_PROVIDED

Constructor Summary

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

Method Summary

float	computeNorm(String fieldName, FieldInvertState state) Deprecated. Computes the normalization value for a field, given the accumulated state of term processing for this field (see FieldInvertState).
float	coord(int overlap, int maxOverlap) Deprecated. Computes a score factor based on the fraction of all query terms that a document contains.
float	idf(int docFreq, int numDocs) Deprecated. Computes a score factor based on a term's document frequency (the number of documents which contain the term).
float	queryNorm(float sumOfSquaredWeights) Deprecated. 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) Deprecated. Calculate a scoring factor based on the data in the payload.
float	sloppyFreq(int distance) Deprecated. Computes the amount of a sloppy phrase match, based on an edit distance.
float	tf(float freq) Deprecated. Computes a score factor based on a term or phrase's frequency in a document.

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

decodeNorm, decodeNormValue, encodeNorm, encodeNormValue, getDefault, getNormDecoder, idfExplain, idfExplain, idfExplain, lengthNorm, setDefault, tf

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SimilarityDelegator

public SimilarityDelegator(Similarity delegee)

Deprecated.

Construct a Similarity that delegates all methods to another.

Parameters:

delegee - the Similarity implementation to delegate to

Method Detail

computeNorm

public float computeNorm(String fieldName,
                         FieldInvertState state)

Deprecated.

Description copied from class: Similarity

Computes 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.

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

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

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

Specified by:

computeNorm in class Similarity

Parameters:

fieldName - field name

state - current processing state for this field

Returns:

the calculated float norm

queryNorm

public float queryNorm(float sumOfSquaredWeights)

Deprecated.

Description copied from class: Similarity

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.

Specified by:

queryNorm in class Similarity

Parameters:

sumOfSquaredWeights - the sum of the squares of query term weights

Returns:

a normalization factor for query weights

tf

public float tf(float freq)

Deprecated.

Description copied from class: Similarity

Computes a score factor based on a term or phrase's frequency in a document. This value is multiplied by the Similarity.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.

Specified by:

tf in class Similarity

Parameters:

freq - the frequency of a term within a document

Returns:

a score factor based on a term's within-document frequency

sloppyFreq

public float sloppyFreq(int distance)

Deprecated.

Description copied from class: Similarity

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.

Specified by:

sloppyFreq in class Similarity

Parameters:

distance - the edit distance of this sloppy phrase match

Returns:

the frequency increment for this match

See Also:

PhraseQuery.setSlop(int)

idf

public float idf(int docFreq,
                 int numDocs)

Deprecated.

Description copied from class: Similarity

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.

Specified by:

idf in class 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

coord

public float coord(int overlap,
                   int maxOverlap)

Deprecated.

Description copied from class: Similarity

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.

Specified by:

coord in class 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

scorePayload

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

Deprecated.

Description copied from class: Similarity

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.

Overrides:

scorePayload in class Similarity

Parameters:

docId - The docId currently being scored. If this value is Similarity.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