Matchcode Optimization:Smith-Waterman-Gotoh

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Matchcode Optimization
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Soundex

Specifics

Summary

A typographical matching algorithm. A variation of the Needleman-Wunch, where it gives a non-linear penalty for inserts and deletes, but less of a penalty for linear inserts and deletes. For example, JNSON has 0.8+0.8 = 1.6 penalty in Needleman-Wunch, but only a 0.8+0.6 = 1.4 penalty in Smith-Waterman-Gotoh. This effectively adds the ‘understanding’ that the keyboarder may have tried to abbreviate one of the words. Because the algorithm creates a 2D array to determine the distance between two strings, results will be more accurate than Fast Near at expense of throughput.

Returns

Boolean ‘match’ if the normalized distance between two strings is less than the configured scale, where distance is defined as the count of the number of incorrect characters, insertions and deletions.

Example Matchcode Component

MCO Algorithm SmithWatermanGotoh.png

Example Data

STRING1 STRING2 RESULT
Johnson Jhnsn Match Found
Mild Hatr Wks Mild Hatter Works Match Found
Deanardo Dinardio Unique
Apco Quik Lube Apco Quik Oil N Lube Match Found



Performance
Slower Faster
Matches
More Matches Greater Accuracy


Recommended Usage

Hybrid or real-time deduping. This works best in matching where the data entry has a proprietary abbreviation rule set.

Not Recommended For

Enterprise size processes.
Gather/scatter, survivorship, or record consolidation of sensitive data.
Quantifiable data or records with proprietary keywords not associated in our knowledgebase tables.

Do Not Use With

UTF-8 data. This algorithm was ported to MatchUp with the assumption that a character equals one byte, and therefore results may not be accurate if the data contains multi-byte characters.