Class 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:
    BM25Similarity
    • Field Detail

      • bm25Similarity

        private final BM25Similarity bm25Similarity
        Deprecated.
    • Constructor Detail

      • 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:
        java.lang.IllegalArgumentException - if k1 is infinite or negative, or if b is not within the range [0..1]
    • Method Detail

      • 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.
      • 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:
        setDiscountOverlaps(boolean)
      • toString

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