org.apache.lucene.search.spell

## Class LuceneLevenshteinDistance

- java.lang.Object
- - org.apache.lucene.search.spell.LuceneLevenshteinDistance

- All Implemented Interfaces:
    StringDistance

      public final class LuceneLevenshteinDistance
      extends Object
      implements StringDistance

  Damerau-Levenshtein (optimal string alignment) implemented in a consistent way as Lucene's FuzzyTermsEnum with the transpositions option enabled. Notes:
  - This metric treats full unicode codepoints as characters
  - This metric scales raw edit distances into a floating point score based upon the shortest of the two terms
  - Transpositions of two adjacent codepoints are treated as primitive edits.
  - Edits are applied in parallel: for example, "ab" and "bca" have distance 3.
  NOTE: this class is not particularly efficient. It is only intended for merging results from multiple DirectSpellCheckers.

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `LuceneLevenshteinDistance()` Creates a new comparator, mimicing the behavior of Lucene's internal edit distance.

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `float` | `getDistance(String target, String other)` Returns a float between 0 and 1 based on how similar the specified strings are to one another.

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

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

- - ### Constructor Detail

    - #### LuceneLevenshteinDistance

          public LuceneLevenshteinDistance()

      Creates a new comparator, mimicing the behavior of Lucene's internal edit distance.

  - ### Method Detail

    - #### getDistance

          public float getDistance(String target,
                          String other)

      Description copied from interface: `StringDistance`
      Returns a float between 0 and 1 based on how similar the specified strings are to one another. Returning a value of 1 means the specified strings are identical and 0 means the string are maximally different.
      Specified by:
        `getDistance` in interface `StringDistance`
      Parameters:
        `target` - The first string.
        `other` - The second string.
      Returns:
        a float between 0 and 1 based on how similar the specified strings are to one another.

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