Package org.apache.lucene.search.similarities

Class MultiSimilarity

java.lang.Object
org.apache.lucene.search.similarities.Similarity
org.apache.lucene.search.similarities.MultiSimilarity
public class MultiSimilarity extends Similarity
Implements the CombSUM method for combining evidence from multiple similarity values described in: Joseph A. Shaw, Edward A. Fox. In Text REtrieval Conference (1993), pp. 243-252

  • Field Details

    • sims

      protected final Similarity[] sims
      the sub-similarities used to create the combined score

  • Constructor Details

    • MultiSimilarity

      public MultiSimilarity(Similarity[] sims)
      Creates a MultiSimilarity which will sum the scores of the provided sims.

  • Method Details

    • computeNorm

      public long computeNorm(FieldInvertState state)
      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.

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

    • computeWeight

      public 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.

    • simScorer

      public Similarity.SimScorer simScorer(Similarity.SimWeight stats, AtomicReaderContext context) throws IOException
      Description copied from class: Similarity
      Creates a new Similarity.SimScorer to score matching documents from a segment of the inverted index.
      Specified by:
      simScorer in class Similarity
      Parameters:
      stats - collection information from Similarity.computeWeight(float, CollectionStatistics, TermStatistics...)
      context - segment of the inverted index to be scored.
      Returns:
      SloppySimScorer for scoring documents across context
      Throws:
      IOException - if there is a low-level I/O error