Class Similarity

    • Constructor Detail

      • Similarity

        public Similarity()
        Sole constructor. (For invocation by subclass constructors, typically implicit.)
    • Method Detail

      • computeNorm

        public abstract long computeNorm​(FieldInvertState state)
        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.

        Parameters:
        state - current processing state for this field
        Returns:
        computed norm value
        WARNING: This API is experimental and might change in incompatible ways in the next release.
      • scorer

        public abstract Similarity.SimScorer scorer​(float boost,
                                                    CollectionStatistics collectionStats,
                                                    TermStatistics... termStats)
        Compute any collection-level weight (e.g. IDF, average document length, etc) needed for scoring a query.
        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.