Matchcode Optimization:Containment

From Melissa Data Wiki
Jump to navigation Jump to search

← MatchUp Hub

Matchcode Optimization Navigation
Matchcode Optimization
First Component
Fuzzy Algorithms
Swap Matching
Blank Matching
Advanced Component Types
Algorithms
Accunear
Alphas
Consonants
Containment
Dice's Coefficient
Double Metaphone
Exact
Fast Near
Frequency
Frequency Near
Jaccard Similarity Coefficient
Jaro
Jaro-Winkler
Longest Common Substring (LCS)
MD Keyboard
Needleman-Wunsch
N-Gram
Numeric
Overlap Coefficient
Phonetex
Smith-Waterman-Gotoh
Soundex
UTF8 Near
Vowels


Containment

Specifics

Matches when one record's component is contained in another record. For example, “Smith” is contained in “Smithfield.”

Summary

This algorithm looks at the record’s component and determines whether that component is contained in the record it is attempting to match.

Returns

Returns true if one record’s component is contained in another record.

Example Matchcode Component

Example Data

STRING1 STRING2 RESULT
Johnson Jhnsn Unique
Mild Hatter Mild Hatter Wks Match
Smith Smithfield Match
Melissa Eli Match



Performance
Slower Faster
Matches
More Matches Greater Accuracy


Recommended Usage

Hybrid Deduper, where a single incoming record can quickly be evaluated independently against each record in an existing large master database.
Batch or Enterprise runs where the first component allows efficient clustering.
Databases where unrecognized keyword variations appear in some of the records.
When the entire value or string of one is contained in the other.

Not Recommended For

Short name string comparison.
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.