public class BooleanSimilarity extends Similarity
discounted overlapsso that the
Similaritycan be changed after the index has been created.
|Constructor and Description|
|Modifier and Type||Method and Description|
Computes the normalization value for a field, given the accumulated state of term processing for this field (see
Compute any collection-level weight (e.g.
Creates a new
public long computeNorm(FieldInvertState state)
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.
public Similarity.SimWeight computeWeight(float boost, CollectionStatistics collectionStats, TermStatistics... termStats)
boost- a multiplicative factor to apply to the produces scores
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.
public Similarity.SimScorer simScorer(Similarity.SimWeight weight, LeafReaderContext context) throws IOException
Similarity.SimScorerto score matching documents from a segment of the inverted index.
weight- collection information from
Similarity.computeWeight(float, CollectionStatistics, TermStatistics...)
context- segment of the inverted index to be scored.
IOException- if there is a low-level I/O error
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