org.apache.lucene.search

Class DefaultSimilarity

java.lang.Object

org.apache.lucene.search.Similarity

org.apache.lucene.search.DefaultSimilarity

All Implemented Interfaces:

Serializable

Direct Known Subclasses:

SweetSpotSimilarity

public class DefaultSimilarity
extends Similarity

Expert: Default scoring implementation.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected boolean	discountOverlaps

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

NO_DOC_ID_PROVIDED

Constructor Summary

Constructors

Constructor and Description
DefaultSimilarity()

Method Summary

Methods

Modifier and Type	Method and Description
float	computeNorm(String field, FieldInvertState state) Implemented as state.getBoost()*lengthNorm(numTerms), where numTerms is FieldInvertState.getLength() if setDiscountOverlaps(boolean) is false, else it's FieldInvertState.getLength() - FieldInvertState.getNumOverlap().
float	coord(int overlap, int maxOverlap) Implemented as overlap / maxOverlap.
boolean	getDiscountOverlaps()
float	idf(int docFreq, int numDocs) Implemented as log(numDocs/(docFreq+1)) + 1.
float	queryNorm(float sumOfSquaredWeights) Implemented as 1/sqrt(sumOfSquaredWeights).
void	setDiscountOverlaps(boolean v) Determines whether overlap tokens (Tokens with 0 position increment) are ignored when computing norm.
float	sloppyFreq(int distance) Implemented as 1 / (distance + 1).
float	tf(float freq) Implemented as sqrt(freq).

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

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

Methods inherited from class java.lang.Object

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

Field Detail

discountOverlaps

protected boolean discountOverlaps

Constructor Detail

DefaultSimilarity

public DefaultSimilarity()

Method Detail

computeNorm

public float computeNorm(String field,
                FieldInvertState state)

Implemented as state.getBoost()*lengthNorm(numTerms), where numTerms is FieldInvertState.getLength() if setDiscountOverlaps(boolean) is false, else it's FieldInvertState.getLength() - FieldInvertState.getNumOverlap().

Specified by:

computeNorm in class Similarity

Parameters:

field - field name

state - current processing state for this field

Returns:

the calculated float norm

WARNING: This API is experimental and might change in incompatible ways in the next release.

queryNorm

public float queryNorm(float sumOfSquaredWeights)

Implemented as 1/sqrt(sumOfSquaredWeights).

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)

Implemented as sqrt(freq).

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)

Implemented as 1 / (distance + 1).

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)

Implemented as log(numDocs/(docFreq+1)) + 1.

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)

Implemented as overlap / maxOverlap.

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

setDiscountOverlaps

public void setDiscountOverlaps(boolean v)

Determines whether overlap tokens (Tokens with 0 position increment) are ignored when computing norm. By default this is true, meaning overlap tokens do not count when computing norms.

See Also:

computeNorm(java.lang.String, org.apache.lucene.index.FieldInvertState)

WARNING: This API is experimental and might change in incompatible ways in the next release.

getDiscountOverlaps

public boolean getDiscountOverlaps()

See Also:

setDiscountOverlaps(boolean)