Package org.apache.lucene.search.similarities

Class LMJelinekMercerSimilarity

java.lang.Object
org.apache.lucene.search.similarities.Similarity
org.apache.lucene.search.similarities.SimilarityBase
org.apache.lucene.search.similarities.LMSimilarity
org.apache.lucene.search.similarities.LMJelinekMercerSimilarity
public class LMJelinekMercerSimilarity extends LMSimilarity
Language model based on the Jelinek-Mercer smoothing method. From Chengxiang Zhai and John Lafferty. 2001. A study of smoothing methods for language models applied to Ad Hoc information retrieval. In Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '01). ACM, New York, NY, USA, 334-342.

The model has a single parameter, λ. According to said paper, the optimal value depends on both the collection and the query. The optimal value is around 0.1 for title queries and 0.7 for long queries.

Values should be between 0 (exclusive) and 1 (inclusive). Values near zero act score more like a conjunction (coordinate level matching), whereas values near 1 behave the opposite (more like pure disjunction).

WARNING: This API is experimental and might change in incompatible ways in the next release.

  • Constructor Details

    • LMJelinekMercerSimilarity

      public LMJelinekMercerSimilarity(LMSimilarity.CollectionModel collectionModel, float lambda)
      Instantiates with the specified collectionModel and λ parameter.

    • LMJelinekMercerSimilarity

      public LMJelinekMercerSimilarity(float lambda)
      Instantiates with the specified λ parameter.

  • Method Details

    • score

      protected double score(BasicStats stats, double freq, double 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, double freq, double 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 LMSimilarity
      Parameters:
      subs - the list of details of the explanation to extend
      stats - the corpus level statistics.
      freq - the term frequency.
      docLen - the document length.

    • explain

      protected Explanation explain(BasicStats stats, Explanation freq, double docLen)
      Description copied from class: SimilarityBase
      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 SimilarityBase.score(BasicStats, double, double) method) and the explanation for the term frequency. Subclasses content with this format may add additional details in SimilarityBase.explain(List, BasicStats, double, double).
      Overrides:
      explain in class SimilarityBase
      Parameters:
      stats - the corpus level statistics.
      freq - the term frequency and its explanation.
      docLen - the document length.
      Returns:
      the explanation.

    • getLambda

      public float getLambda()
      Returns the λ parameter.

    • getName

      public String getName()
      Description copied from class: LMSimilarity
      Returns the name of the LM method. The values of the parameters should be included as well.

      Used in LMSimilarity.toString().

      Specified by:
      getName in class LMSimilarity