public class AssertingSimilarity extends Similarity
Similarity.SimScorer
Constructor and Description |
---|
AssertingSimilarity(Similarity delegate) |
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.SimScorer |
scorer(float boost,
CollectionStatistics collectionStats,
TermStatistics... termStats)
Compute any collection-level weight (e.g.
|
java.lang.String |
toString() |
public AssertingSimilarity(Similarity delegate)
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.
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
and n2
so that
Long.compareUnsigned(n1, n2) > 0
then
SimScorer.score(freq, n1) <= SimScorer.score(freq, n2)
for any legal freq
.
0
is not a legal norm, so 1
is the norm that produces
the highest scores.
computeNorm
in class Similarity
state
- current processing state for this fieldpublic Similarity.SimScorer scorer(float boost, CollectionStatistics collectionStats, TermStatistics... termStats)
Similarity
scorer
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 java.lang.String toString()
toString
in class java.lang.Object
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