org.apache.lucene.search.similarities

Class DFRSimilarity



  • public class DFRSimilarity
    extends SimilarityBase
    Implements the divergence from randomness (DFR) framework introduced in Gianni Amati and Cornelis Joost Van Rijsbergen. 2002. Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM Trans. Inf. Syst. 20, 4 (October 2002), 357-389.

    The DFR scoring formula is composed of three separate components: the basic model, the aftereffect and an additional normalization component, represented by the classes BasicModel, AfterEffect and Normalization, respectively. The names of these classes were chosen to match the names of their counterparts in the Terrier IR engine.

    To construct a DFRSimilarity, you must specify the implementations for all three components of DFR:

    1. BasicModel: Basic model of information content:
    2. AfterEffect: First normalization of information gain:
    3. Normalization: Second (length) normalization:

    Note that qtf, the multiplicity of term-occurrence in the query, is not handled by this implementation.

    See Also:
    BasicModel, AfterEffect, Normalization
    • Constructor Detail

    • Method Detail

      • score

        protected float score(BasicStats stats,
                              float freq,
                              float docLen)
        Description copied from class: SimilarityBase
        Scores the document doc.

        Subclasses must apply their scoring formula in this class.

        Specified by:
        score in class SimilarityBase
        Parameters:
        stats - the corpus level statistics.
        freq - the term frequency.
        docLen - the document length.
        Returns:
        the score.
      • explain

        protected void explain(List<Explanation> subs,
                               BasicStats stats,
                               int doc,
                               float freq,
                               float docLen)
        Description copied from class: SimilarityBase
        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.

        Overrides:
        explain in class SimilarityBase
        Parameters:
        subs - the list of details of the explanation to extend
        stats - the corpus level statistics.
        doc - the document id.
        freq - the term frequency.
        docLen - the document length.
      • toString

        public String toString()
        Description copied from class: SimilarityBase
        Subclasses must override this method to return the name of the Similarity and preferably the values of parameters (if any) as well.
        Specified by:
        toString in class SimilarityBase