text.jaroWinkler

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Description

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Syntax

flex.text.jaroWinkler(string1, string2)

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Parameters

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Returns

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

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Examples

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Example 1: Name Matching

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

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

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Example 2: Fuzzy Name Search

// 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

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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

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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

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See Also

• text.levenshtein - Edit distance metric for string comparison
• sim.jaccard - Set-based similarity

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Frequently Asked Questions