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Normalized Levenshtein distance¤

Normalized Levenshtein distance. Divides the edit distance by the length of the longer string.

Characteristics¤

This distance measure is normalized, i.e., all distances are between 0 (exact match) and 1 (no similarity).

Compares single values (as opposed to sequences of values). If multiple values are provided, all values are compared and the lowest distance is returned.

Examples¤

Notation: List of values are represented via square brackets. Example: [first, second] represents a list of two values “first” and “second”.

Returns 0 for equal strings:

  • Input values:

    • Source: [John]
    • Target: [John]

  • Returns: 0.0

Returns 1/4 if two strings of length 4 differ by one edit operation:

  • Input values:

    • Source: [John]
    • Target: [Jxhn]

  • Returns: 0.25

Normalizes the edit distance by the length of the longer string:

  • Input values:

    • Source: [John]
    • Target: [Jhn]

  • Returns: 0.25

Returns the maximum distance of 1 for completely different strings:

  • Input values:

    • Source: [John]
    • Target: [Clara]

  • Returns: 1.0

Parameter¤

None

Advanced Parameter¤

Q-grams size¤

The size of the q-grams to be indexed. Setting this to zero will disable indexing.

  • ID: qGramsSize
  • Datatype: int
  • Default Value: 2

Min char¤

The minimum character that is used for indexing

  • ID: minChar
  • Datatype: char
  • Default Value: 0

Max char¤

The maximum character that is used for indexing

  • ID: maxChar
  • Datatype: char
  • Default Value: z
  • levenshteinDistance — The Levenshtein distance plugin counts the minimum edits needed to transform one string into the other. The normalized Levenshtein distance plugin divides that count by the length of the longer string, so the distance is comparable regardless of how long the strings are.

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