Package org.apache.lucene.search.similarity

Class LegacyBM25Similarity

java.lang.Object
org.apache.lucene.search.similarities.Similarity
org.apache.lucene.search.similarity.LegacyBM25Similarity
@Deprecated public final class LegacyBM25Similarity extends Similarity
Deprecated.
BM25Similarity should be used instead
Similarity that behaves like BM25Similarity while also applying the k1+1 factor to the numerator of the scoring formula
See Also:

  • Field Details

    • bm25Similarity

      private final BM25Similarity bm25Similarity
      Deprecated.

  • Constructor Details

    • LegacyBM25Similarity

      public LegacyBM25Similarity()
      Deprecated.
      BM25 with these default values:
      • k1 = 1.2
      • b = 0.75

    • LegacyBM25Similarity

      public LegacyBM25Similarity(float k1, float b)
      Deprecated.
      BM25 with the supplied parameter values.
      Parameters:
      k1 - Controls non-linear term frequency normalization (saturation).
      b - Controls to what degree document length normalizes tf values.
      Throws:
      IllegalArgumentException - if k1 is infinite or negative, or if b is not within the range [0..1]

  • Method Details

    • computeNorm

      public long computeNorm(FieldInvertState state)
      Deprecated.
      Description copied from class: Similarity
      Computes the normalization value for a field, given the accumulated state of term processing for this field (see 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.

      Specified by:
      computeNorm in class Similarity
      Parameters:
      state - current processing state for this field
      Returns:
      computed norm value

    • scorer

      public Similarity.SimScorer scorer(float boost, CollectionStatistics collectionStats, TermStatistics... termStats)
      Deprecated.
      Description copied from class: Similarity
      Compute any collection-level weight (e.g. IDF, average document length, etc) needed for scoring a query.
      Specified by:
      scorer in class Similarity
      Parameters:
      boost - a multiplicative factor to apply to the produces scores
      collectionStats - 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.
      Returns:
      SimWeight object with the information this Similarity needs to score a query.

    • getK1

      public final float getK1()
      Deprecated.
      Returns the k1 parameter
      See Also:

    • getB

      public final float getB()
      Deprecated.
      Returns the b parameter
      See Also:

    • setDiscountOverlaps

      public void setDiscountOverlaps(boolean v)
      Deprecated.
      Sets whether overlap tokens (Tokens with 0 position increment) are ignored when computing norm. By default this is true, meaning overlap tokens do not count when computing norms.

    • getDiscountOverlaps

      public boolean getDiscountOverlaps()
      Deprecated.
      Returns true if overlap tokens are discounted from the document's length.
      See Also:

    • toString

      public String toString()
      Deprecated.
      Overrides:
      toString in class Object