Class Similarity.SimScorer

Enclosing class:

public abstract static class Similarity.SimScorer extends Object
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.
  • Constructor Details

    • SimScorer

      protected SimScorer()
      Sole constructor. (For invocation by subclass constructors.)
  • Method Details

    • score

      public abstract float 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).

      freq - sloppy term frequency, must be finite and positive
      norm - encoded normalization factor or 1 if norms are disabled
      document's score
    • explain

      public Explanation explain(Explanation freq, long norm)
      Explain the score for a single document
      freq - Explanation of how the sloppy term frequency was computed
      norm - encoded normalization factor, as returned by Similarity.computeNorm(org.apache.lucene.index.FieldInvertState), or 1 if norms are disabled
      document's score