public class BooleanSimilarity extends Similarity
SimilarityBase
and BM25Similarity
with
discounted overlaps
so that the Similarity
can be changed after the index has been
created.Modifier and Type | Class and Description |
---|---|
private static class |
BooleanSimilarity.BooleanWeight |
Similarity.SimScorer, Similarity.SimWeight
Modifier and Type | Field and Description |
---|---|
private static Similarity |
BM25_SIM |
Constructor and Description |
---|
BooleanSimilarity()
Sole constructor
|
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(float boost,
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. |
private static final Similarity BM25_SIM
public long computeNorm(FieldInvertState state)
Similarity
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.
computeNorm
in class Similarity
state
- current processing state for this fieldpublic Similarity.SimWeight computeWeight(float boost, CollectionStatistics collectionStats, TermStatistics... termStats)
Similarity
computeWeight
in class Similarity
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.public Similarity.SimScorer simScorer(Similarity.SimWeight weight, LeafReaderContext context) throws java.io.IOException
Similarity
Similarity.SimScorer
to score matching documents from a segment of the inverted index.simScorer
in class Similarity
weight
- collection information from Similarity.computeWeight(float, CollectionStatistics, TermStatistics...)
context
- segment of the inverted index to be scored.context
java.io.IOException
- if there is a low-level I/O error