Package org.apache.lucene.search.similarities

Class MultiSimilarity

java.lang.Object

org.apache.lucene.search.similarities.Similarity

org.apache.lucene.search.similarities.MultiSimilarity

public class MultiSimilarity
extends Similarity

Implements the CombSUM method for combining evidence from multiple similarity values described in: Joseph A. Shaw, Edward A. Fox. In Text REtrieval Conference (1993), pp. 243-252

Nested Class Summary

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

Similarity.SimScorer, Similarity.SimWeight

Field Summary

Fields

Modifier and Type	Field	Description
protected Similarity[]	sims	the sub-similarities used to create the combined score

Constructor Summary

Constructors

Constructor	Description
MultiSimilarity(Similarity[] sims)	Creates a MultiSimilarity which will sum the scores of the provided sims.

Method Summary

Modifier and Type	Method	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(float queryBoost, CollectionStatistics collectionStats, TermStatistics... termStats)	Compute any collection-level weight (e.g.
Similarity.SimScorer	simScorer(Similarity.SimWeight stats, AtomicReaderContext 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

Field Detail

sims

protected final Similarity[] sims

the sub-similarities used to create the combined score

Constructor Detail

MultiSimilarity

public MultiSimilarity(Similarity[] sims)

Creates a MultiSimilarity which will sum the scores of the provided sims.

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(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 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:

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