org.apache.lucene.search.similarities

Class BooleanSimilarity

java.lang.Object

org.apache.lucene.search.similarities.Similarity

org.apache.lucene.search.similarities.BooleanSimilarity

public class BooleanSimilarity
extends Similarity

Simple similarity that gives terms a score that is equal to their query boost. This similarity is typically used with disabled norms since neither document statistics nor index statistics are used for scoring. That said, if norms are enabled, they will be computed the same way as SimilarityBase and BM25Similarity with discounted overlaps so that the Similarity can be changed after the index has been created.

Nested Class Summary

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

Similarity.SimScorer, Similarity.SimWeight

Constructor Summary

Constructors

Constructor and Description
BooleanSimilarity() Sole constructor

Method Summary

Modifier and Type	Method and Description
long	computeNorm(FieldInvertState state) Computes the normalization value for a field, given the accumulated state of term processing for this field (see FieldInvertState).
Similarity.SimWeight	computeWeight(CollectionStatistics collectionStats, TermStatistics... termStats) Compute any collection-level weight (e.g.
Similarity.SimScorer	simScorer(Similarity.SimWeight weight, LeafReaderContext context) Creates a new Similarity.SimScorer to score matching documents from a segment of the inverted index.

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

coord, queryNorm

Methods inherited from class java.lang.Object

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

Constructor Detail

BooleanSimilarity

public BooleanSimilarity()

Sole constructor

Method Detail

computeNorm

public long computeNorm(FieldInvertState state)

Description copied from class: Similarity

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

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

Specified by:

computeNorm in class Similarity

Parameters:

state - current processing state for this field

Returns:

computed norm value

computeWeight

public Similarity.SimWeight computeWeight(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:

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 weight,
                                      LeafReaderContext context)
                               throws 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:

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

context - segment of the inverted index to be scored.

Returns:

SloppySimScorer for scoring documents across context

Throws:

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