Package org.apache.lucene.search.similarities

Class SimilarityBase

java.lang.Object

org.apache.lucene.search.similarities.Similarity

org.apache.lucene.search.similarities.SimilarityBase

Direct Known Subclasses:

DFRSimilarity, IBSimilarity, LMSimilarity

public abstract class SimilarityBase
extends Similarity

A subclass of Similarity that provides a simplified API for its descendants. Subclasses are only required to implement the score(org.apache.lucene.search.similarities.BasicStats, float, float) and toString() methods. Implementing explain(Explanation, BasicStats, int, float, float) is optional, inasmuch as SimilarityBase already provides a basic explanation of the score and the term frequency. However, implementers of a subclass are encouraged to include as much detail about the scoring method as possible.

Note: multi-word queries such as phrase queries are scored in a different way than Lucene's default ranking algorithm: whereas it "fakes" an IDF value for the phrase as a whole (since it does not know it), this class instead scores phrases as a summation of the individual term scores.

Nested Class Summary

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

Similarity.SimScorer, Similarity.SimWeight

Constructor Summary

Constructors

Constructor	Description
SimilarityBase()	Sole constructor.

Method Summary

Modifier and Type	Method	Description
long	computeNorm(FieldInvertState state)	Encodes the document length in the same way as TFIDFSimilarity.
Similarity.SimWeight	computeWeight(float queryBoost, CollectionStatistics collectionStats, TermStatistics... termStats)	Compute any collection-level weight (e.g.
boolean	getDiscountOverlaps()	Returns true if overlap tokens are discounted from the document's length.
static double	log2(double x)	Returns the base two logarithm of x.
void	setDiscountOverlaps(boolean v)	Determines whether overlap tokens (Tokens with 0 position increment) are ignored when computing norm.
Similarity.SimScorer	simScorer(Similarity.SimWeight stats, AtomicReaderContext context)	Creates a new Similarity.SimScorer to score matching documents from a segment of the inverted index.
abstract java.lang.String	toString()	Subclasses must override this method to return the name of the Similarity and preferably the values of parameters (if any) as well.

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

coord, queryNorm

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

SimilarityBase

public SimilarityBase()

Sole constructor. (For invocation by subclass constructors, typically implicit.)

Method Detail

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(org.apache.lucene.index.FieldInvertState)

getDiscountOverlaps

public boolean getDiscountOverlaps()

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

See Also:

setDiscountOverlaps(boolean)

computeWeight

public final Similarity.SimWeight computeWeight(float queryBoost,
                                                CollectionStatistics collectionStats,
                                                TermStatistics... termStats)

Description copied from class: Similarity

Compute any collection-level weight (e.g. IDF, average document length, etc) needed for scoring a query.

Specified by:

computeWeight in class Similarity

Parameters:

queryBoost - the query-time boost.

collectionStats - collection-level statistics, such as the number of tokens in the collection.

termStats - term-level statistics, such as the document frequency of a term across the collection.

Returns:

SimWeight object with the information this Similarity needs to score a query.

simScorer

public Similarity.SimScorer simScorer(Similarity.SimWeight stats,
                                      AtomicReaderContext context)
                               throws java.io.IOException

Description copied from class: Similarity

Creates a new Similarity.SimScorer to score matching documents from a segment of the inverted index.

Specified by:

simScorer in class Similarity

Parameters:

stats - collection information from Similarity.computeWeight(float, CollectionStatistics, TermStatistics...)

context - segment of the inverted index to be scored.

Returns:

SloppySimScorer for scoring documents across context

Throws:

java.io.IOException - if there is a low-level I/O error

toString

public abstract java.lang.String toString()

Subclasses must override this method to return the name of the Similarity and preferably the values of parameters (if any) as well.

Overrides:

toString in class java.lang.Object

computeNorm

public long computeNorm(FieldInvertState state)

Encodes the document length in the same way as TFIDFSimilarity.

Specified by:

computeNorm in class Similarity

Parameters:

state - current processing state for this field

Returns:

computed norm value

log2

public static double log2(double x)

Returns the base two logarithm of x.