public abstract static class Similarity.SimScorer extends Object
Similarity
should
subclass SimWeight
and define the statistics they require in the
subclass. Examples include idf, average field length, etc.Modifier | Constructor and Description |
---|---|
protected |
SimScorer()
Sole constructor.
|
Modifier and Type | Method and Description |
---|---|
Explanation |
explain(Explanation freq,
long norm)
Explain the score for a single document
|
abstract float |
score(float freq,
long norm)
Score a single document.
|
protected SimScorer()
public abstract float score(float freq, long norm)
freq
is the document-term sloppy
frequency and must be finite and positive. norm
is the
encoded normalization factor as computed by
Similarity.computeNorm(FieldInvertState)
at index time, or
1
if norms are disabled. norm
is never 0
.
Score must not decrease when freq
increases, ie. if
freq1 > freq2
, then score(freq1, norm) >=
score(freq2, norm)
for any value of norm
that may be produced
by Similarity.computeNorm(FieldInvertState)
.
Score must not increase when the unsigned norm
increases, ie. if
Long.compareUnsigned(norm1, norm2) > 0
then
score(freq, norm1) <= score(freq, norm2)
for any legal
freq
.
As a consequence, the maximum score that this scorer can produce is bound
by score(Float.MAX_VALUE, 1)
.
freq
- sloppy term frequency, must be finite and positivenorm
- encoded normalization factor or 1
if norms are disabledpublic Explanation explain(Explanation freq, long norm)
freq
- Explanation of how the sloppy term frequency was computednorm
- encoded normalization factor, as returned by Similarity.computeNorm(org.apache.lucene.index.FieldInvertState)
, or 1
if norms are disabledCopyright © 2000-2021 Apache Software Foundation. All Rights Reserved.