text.jaroWinkler

Description

Computes the Jaro-Winkler similarity between two strings. This metric is particularly effective for short strings like names and addresses. It gives more favorable ratings to strings that match from the beginning. Returns a value between 0 (no similarity) and 1 (exact match).

Syntax 

flex.text.jaroWinkler(string1, string2)

Parameters

| Parameter | Type | Required | Description | |———–|——|———-|————-| | string1 | string | Yes | The first string to compare | | string2 | string | Yes | The second string to compare |

Returns

Type: number (float)

A similarity score between 0 and 1:

  • 1.0 indicates an exact match
  • 0.0 indicates no similarity
  • Higher values indicate greater similarity

Examples

Example 1: Name Matching 

// Compare similar names
RETURN flex.text.jaroWinkler('Martha', 'Marhta') AS similarity

Output:

similarity
----------
0.961

// Find people with names similar to "William"
MATCH (p:Person)
WHERE flex.text.jaroWinkler(p.firstName, 'William') > 0.85
RETURN p.firstName, p.lastName, flex.text.jaroWinkler(p.firstName, 'William') AS score
ORDER BY score DESC

Example 3: Deduplication by Company Name 

// Find potential duplicate company records
MATCH (c1:Company)
MATCH (c2:Company)
WHERE id(c1) < id(c2)
WITH c1, c2, flex.text.jaroWinkler(c1.name, c2.name) AS similarity
WHERE similarity > 0.9
RETURN c1.name, c2.name, similarity
ORDER BY similarity DESC

Notes

  • Particularly effective for short strings (names, addresses)
  • Gives higher weight to strings that match from the beginning
  • Handles null values by returning appropriate default values
  • Case-sensitive comparison
  • More forgiving than exact match but stricter than pure Jaro similarity
  • Commonly used in record linkage and deduplication tasks

See Also