Class 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.

  • 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 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(Explanation expl, 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 LMSimilarity
      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.
    • 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