org.apache.lucene.search.similarities

Class DefaultSimilarity

java.lang.Object

org.apache.lucene.search.similarities.Similarity

org.apache.lucene.search.similarities.TFIDFSimilarity

org.apache.lucene.search.similarities.DefaultSimilarity

public class DefaultSimilarity
extends TFIDFSimilarity

Expert: Default scoring implementation.

Nested Class Summary

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

Similarity.ExactSimScorer, Similarity.SimWeight, Similarity.SloppySimScorer

Field Summary

Fields

Modifier and Type	Field and Description
protected boolean	discountOverlaps True if overlap tokens (tokens with a position of increment of zero) are discounted from the document's length.

Constructor Summary

Constructors

Constructor and Description
DefaultSimilarity() Sole constructor: parameter-free

Method Summary

Methods

Modifier and Type	Method and Description
float	coord(int overlap, int maxOverlap) Implemented as overlap / maxOverlap.
boolean	getDiscountOverlaps() Returns true if overlap tokens are discounted from the document's length.
float	idf(long docFreq, long numDocs) Implemented as log(numDocs/(docFreq+1)) + 1.
float	lengthNorm(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	queryNorm(float sumOfSquaredWeights) Implemented as 1/sqrt(sumOfSquaredWeights).
float	scorePayload(int doc, int start, int end, BytesRef payload) The default implementation returns 1
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).
String	toString()

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

computeNorm, computeWeight, decodeNormValue, encodeNormValue, exactSimScorer, idfExplain, idfExplain, sloppySimScorer, tf

Methods inherited from class java.lang.Object

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

Field Detail

discountOverlaps

protected boolean discountOverlaps

True if overlap tokens (tokens with a position of increment of zero) are discounted from the document's length.

Constructor Detail

DefaultSimilarity

public DefaultSimilarity()

Sole constructor: parameter-free

Method Detail

coord

public float coord(int overlap,
          int maxOverlap)

Implemented as overlap / maxOverlap.

Specified by:

coord in class TFIDFSimilarity

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

queryNorm

public float queryNorm(float sumOfSquaredWeights)

Implemented as 1/sqrt(sumOfSquaredWeights).

Specified by:

queryNorm in class TFIDFSimilarity

Parameters:

sumOfSquaredWeights - the sum of the squares of query term weights

Returns:

a normalization factor for query weights

lengthNorm

public float lengthNorm(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:

lengthNorm in class TFIDFSimilarity

Parameters:

state - statistics of the current field (such as length, boost, etc)

Returns:

an index-time normalization value

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

tf

public float tf(float freq)

Implemented as sqrt(freq).

Specified by:

tf in class TFIDFSimilarity

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 TFIDFSimilarity

Parameters:

distance - the edit distance of this sloppy phrase match

Returns:

the frequency increment for this match

See Also:

PhraseQuery.setSlop(int)

scorePayload

public float scorePayload(int doc,
                 int start,
                 int end,
                 BytesRef payload)

The default implementation returns 1

Specified by:

scorePayload in class TFIDFSimilarity

Parameters:

doc - The docId currently being scored.

start - The start position of the payload

end - The end position of the payload

payload - The payload byte array to be scored

Returns:

An implementation dependent float to be used as a scoring factor

idf

public float idf(long docFreq,
        long numDocs)

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

Specified by:

idf in class TFIDFSimilarity

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

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:

TFIDFSimilarity.computeNorm(org.apache.lucene.index.FieldInvertState)

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

getDiscountOverlaps

public boolean getDiscountOverlaps()

Returns true if overlap tokens are discounted from the document's length.

See Also:

setDiscountOverlaps(boolean)

toString

public String toString()

Overrides:

toString in class Object