Stores the weight for a query across the indexed collection. This abstract implementation is
empty; descendants of Similarity should subclass SimWeight and define the
statistics they require in the subclass. Examples include idf, average field length, etc.
Return a BulkSimScorer that produces the exact same scores as this SimScorer
but is more efficient at bulk-computing scores.
NOTE: The returned instance is not thread-safe.
explain(org.apache.lucene.search.Explanation freq, long norm)Explain the score for a single document
| name | type | description |
|---|---|---|
| freq | org.apache.lucene.search.Explanation | Explanation of how the sloppy term frequency was computed |
| norm | long | encoded normalization factor, as returned by Similarity#computeNorm, or
1 if norms are disabled |
Returns: document's score
score(float freq, long norm)Score a single document. 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).
| name | type | description |
|---|---|---|
| freq | float | sloppy term frequency, must be finite and positive |
| norm | long | encoded normalization factor or 1 if norms are disabled |
Returns: document's score