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.

- - ### Nested Class Summary

    - ### Nested classes/interfaces inherited from class org.apache.lucene.search.similarities.LMSimilarity

      `LMSimilarity.CollectionModel, LMSimilarity.DefaultCollectionModel, LMSimilarity.LMStats`

    - ### Nested classes/interfaces inherited from class org.apache.lucene.search.similarities.Similarity

      `Similarity.SimScorer`

  - ### Field Summary

    - ### Fields inherited from class org.apache.lucene.search.similarities.LMSimilarity

      `collectionModel`

    - ### Fields inherited from class org.apache.lucene.search.similarities.SimilarityBase

      `discountOverlaps`

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `LMJelinekMercerSimilarity(float lambda)` Instantiates with the specified λ parameter.
    `LMJelinekMercerSimilarity(LMSimilarity.CollectionModel collectionModel, float lambda)` Instantiates with the specified collectionModel and λ parameter.

  - ### Method Summary

    All Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `protected Explanation` | `explain(BasicStats stats, Explanation freq, double docLen)` Explains the score.
    `protected void` | `explain(List<Explanation> subs, BasicStats stats, double freq, double docLen)` Subclasses should implement this method to explain the score.
    `float` | `getLambda()` Returns the λ parameter.
    `String` | `getName()` Returns the name of the LM method.
    `protected double` | `score(BasicStats stats, double freq, double docLen)` Scores the document `doc`.

    - ### Methods inherited from class org.apache.lucene.search.similarities.LMSimilarity

      `fillBasicStats, newStats, toString`

    - ### Methods inherited from class org.apache.lucene.search.similarities.SimilarityBase

      `computeNorm, getDiscountOverlaps, log2, scorer, setDiscountOverlaps`

    - ### Methods inherited from class java.lang.Object

      `clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait`

- - ### Constructor Detail

    - #### 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 Detail

    - #### 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`

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