Class BooleanSimilarity
java.lang.Object
org.apache.lucene.search.similarities.Similarity
org.apache.lucene.search.similarities.BooleanSimilarity
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
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionlong
computeNorm
(FieldInvertState state) Computes the normalization value for a field, given the accumulated state of term processing for this field (seeFieldInvertState
).scorer
(float boost, CollectionStatistics collectionStats, TermStatistics... termStats) Compute any collection-level weight (e.g.
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Constructor Details
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BooleanSimilarity
public BooleanSimilarity()Sole constructor
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Method Details
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computeNorm
Description copied from class:Similarity
Computes the normalization value for a field, given the accumulated state of term processing for this field (seeFieldInvertState
).Matches in longer fields are less precise, so implementations of this method usually set smaller values when
state.getLength()
is large, and larger values whenstate.getLength()
is small.Note that for a given term-document frequency, greater unsigned norms must produce scores that are lower or equal, ie. for two encoded norms
n1
andn2
so thatLong.compareUnsigned(n1, n2) > 0
thenSimScorer.score(freq, n1) <= SimScorer.score(freq, n2)
for any legalfreq
.0
is not a legal norm, so1
is the norm that produces the highest scores.- Specified by:
computeNorm
in classSimilarity
- Parameters:
state
- current processing state for this field- Returns:
- computed norm value
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scorer
public Similarity.SimScorer scorer(float boost, 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:
scorer
in classSimilarity
- Parameters:
boost
- a multiplicative factor to apply to the produces scorescollectionStats
- 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.
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