Difference between revisions of "Matchcode Optimization:Jaro"

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==Jaro==
 
==Jaro==
 
===Specifics===
 
===Specifics===
Winkler Distance
+
:Winkler Distance
*http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance
+
:*http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance
  
 
===Summary===
 
===Summary===
Gathers common characters (in order) between the two strings, then counts transpositions between the two common strings.
+
:Gathers common characters (in order) between the two strings, then counts transpositions between the two common strings.
  
 
===Returns===
 
===Returns===
Percentage of similarity
+
:Percentage of similarity
  
1/3 * (common/len1 + common/len2 + (common-transpositions)/common)
+
:1/3 * (common/len1 + common/len2 + (common-transpositions)/common)
  
Where common is defined as a character match if the distance within the 2 strings is within the algorithms defined range. Transpositions are defined as:  a character match  (but different sequence order) /2
+
:Where common is defined as a character match if the distance within the 2 strings is within the algorithms defined range. Transpositions are defined as:  a character match  (but different sequence order) /2
  
 
===Example Matchcode Component===
 
===Example Matchcode Component===
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{{ExampleDataTableV1|STRING1|STRING2|RESULT
 
{{ExampleDataTableV1|STRING1|STRING2|RESULT
 
|AdditionalRows=
 
|AdditionalRows=
{{EDTRow|White|Johnson|Jhnsn|Match Found}}
+
{{EDTRow|Green|Johnson|Jhnsn|Match Found}}
{{EDTRow|White|Maguire|Mcguire|Match Found}}
+
{{EDTRow|Green|Maguire|Mcguire|Match Found}}
{{EDTRow|Green|Beaumarchais|Bumarchay|Unique}}
+
{{EDTRow|White|Beaumarchais|Bumarchay|Unique}}
{{EDTRow|Green|Deanardo|Dinardio|Unique}}
+
{{EDTRow|White|Deanardo|Dinardio|Unique}}
 
}}
 
}}
  
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===Recommended Usage===
 
===Recommended Usage===
Hybrid deduper, where a single incoming record can quickly be evaluated independently against each record in an existing large master database.
+
:Hybrid deduper, where a single incoming record can quickly be evaluated independently against each record in an existing large master database.
  
Databases created with abbreviations or similar word substitutions.
+
:Databases created with abbreviations or similar word substitutions.
  
 
===Not Recommended For===
 
===Not Recommended For===
Large or Enterprise level batch runs. Since the algorithm must be evaluated for each record comparison, throughput will be very slow.
+
:Large or Enterprise level batch runs. Since the algorithm must be evaluated for each record comparison, throughput will be very slow.
  
Databases created via real-time data entry where audio likeness errors are introduced.
+
:Databases created via real-time data entry where audio likeness errors are introduced.
  
 
===Do Not Use With===
 
===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.
+
: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.
  
  
 
[[Category:MatchUp Hub]]
 
[[Category:MatchUp Hub]]
 
[[Category:Matchcode Optimization]]
 
[[Category:Matchcode Optimization]]

Latest revision as of 14:23, 27 September 2018

← 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


Jaro

Specifics

Winkler Distance

Summary

Gathers common characters (in order) between the two strings, then counts transpositions between the two common strings.

Returns

Percentage of similarity
1/3 * (common/len1 + common/len2 + (common-transpositions)/common)
Where common is defined as a character match if the distance within the 2 strings is within the algorithms defined range. Transpositions are defined as: a character match (but different sequence order) /2

Example Matchcode Component

MCO Algorithm Jaro.png

Example Data

STRING1 STRING2 RESULT
Johnson Jhnsn Match Found
Maguire Mcguire Match Found
Beaumarchais Bumarchay Unique
Deanardo Dinardio Unique



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.
Databases created with abbreviations or similar word substitutions.

Not Recommended For

Large or Enterprise level batch runs. Since the algorithm must be evaluated for each record comparison, throughput will be very slow.
Databases created via real-time data entry where audio likeness errors are introduced.

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.