Package org.apache.lucene.search.similarities

Class SimilarityBase

  • Direct Known Subclasses:
    DFRSimilarity, IBSimilarity, LMSimilarity
    public abstract class SimilarityBase
extends Similarity
    A subclass of Similarity that provides a simplified API for its descendants. Subclasses are only required to implement the score(org.apache.lucene.search.similarities.BasicStats, float, float) and toString() methods. Implementing explain(Explanation, BasicStats, int, float, float) is optional, inasmuch as SimilarityBase already provides a basic explanation of the score and the term frequency. However, implementers of a subclass are encouraged to include as much detail about the scoring method as possible.

    Note: multi-word queries such as phrase queries are scored in a different way than Lucene's default ranking algorithm: whereas it "fakes" an IDF value for the phrase as a whole (since it does not know it), this class instead scores phrases as a summation of the individual term scores.

    • Field Detail

      • discountOverlaps

        protected boolean discountOverlaps
        True if overlap tokens (tokens with a position of increment of zero) are discounted from the document's length.

    • Constructor Detail

      • SimilarityBase

        public SimilarityBase()
        Sole constructor. (For invocation by subclass constructors, typically implicit.)

    • Method Detail

      • setDiscountOverlaps

        public void setDiscountOverlaps​(boolean v)
        Determines 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.
        See Also:
        computeNorm(org.apache.lucene.index.FieldInvertState)

      • getDiscountOverlaps

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

      • computeWeight

        public final Similarity.SimWeight computeWeight​(float queryBoost,
                                                CollectionStatistics collectionStats,
                                                TermStatistics... termStats)
        Description copied from class: Similarity
        Compute any collection-level weight (e.g. IDF, average document length, etc) needed for scoring a query.
        Specified by:
        computeWeight in class Similarity
        Parameters:
        queryBoost - the query-time boost.
        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.

      • newStats

        protected BasicStats newStats​(String field,
                              float queryBoost)
        Factory method to return a custom stats object

      • fillBasicStats

        protected void fillBasicStats​(BasicStats stats,
                              CollectionStatistics collectionStats,
                              TermStatistics termStats)
        Fills all member fields defined in BasicStats in stats. Subclasses can override this method to fill additional stats.

      • score

        protected abstract float score​(BasicStats stats,
                               float freq,
                               float docLen)
        Scores the document doc.

        Subclasses must apply their scoring formula in this class.

        Parameters:
        stats - the corpus level statistics.
        freq - the term frequency.
        docLen - the document length.
        Returns:
        the score.

      • explain

        protected void explain​(Explanation expl,
                       BasicStats stats,
                       int doc,
                       float freq,
                       float docLen)
        Subclasses should implement this method to explain the score. expl already contains the score, the name of the class and the doc id, as well as the term frequency and its explanation; subclasses can add additional clauses to explain details of their scoring formulae.

        The default implementation does nothing.

        Parameters:
        expl - the explanation to extend with details.
        stats - the corpus level statistics.
        doc - the document id.
        freq - the term frequency.
        docLen - the document length.

      • explain

        protected Explanation explain​(BasicStats stats,
                              int doc,
                              Explanation freq,
                              float docLen)
        Explains the score. The implementation here provides a basic explanation in the format score(name-of-similarity, doc=doc-id, freq=term-frequency), computed from:, and attaches the score (computed via the score(BasicStats, float, float) method) and the explanation for the term frequency. Subclasses content with this format may add additional details in explain(Explanation, BasicStats, int, float, float).
        Parameters:
        stats - the corpus level statistics.
        doc - the document id.
        freq - the term frequency and its explanation.
        docLen - the document length.
        Returns:
        the explanation.

      • toString

        public abstract String toString()
        Subclasses must override this method to return the name of the Similarity and preferably the values of parameters (if any) as well.
        Overrides:
        toString in class Object

      • computeNorm

        public long computeNorm​(FieldInvertState state)
        Encodes the document length in the same way as TFIDFSimilarity.
        Specified by:
        computeNorm in class Similarity
        Parameters:
        state - current processing state for this field
        Returns:
        computed norm value

      • decodeNormValue

        protected float decodeNormValue​(byte norm)
        Decodes a normalization factor (document length) stored in an index.
        See Also:
        encodeNormValue(float,float)

      • encodeNormValue

        protected byte encodeNormValue​(float boost,
                               float length)
        Encodes the length to a byte via SmallFloat.

      • log2

        public static double log2​(double x)
        Returns the base two logarithm of x.