Matchcode Optimization:Phonetex - Revision history

Admin at 14:30, 27 September 2018

2018-09-27T14:30:11Z

← Older revision		Revision as of 14:30, 27 September 2018
Line 5:		Line 5:
	==Phonetex==		==Phonetex==
	===Specifics===		===Specifics===
	(pronounced "Fo-NEH-tex") An auditory matching algorithm developed by Melissa Data. It works best in matching words that sound alike but are spelled differently. It is an improvement over the Soundex algorithm.		:(pronounced "Fo-NEH-tex") An auditory matching algorithm developed by Melissa Data. It works best in matching words that sound alike but are spelled differently. It is an improvement over the Soundex algorithm.

	===Summary===		===Summary===
	A variation of the SoundEx Algorithm. PhonetEx takes into account letter combinations that sound alike, particularly at the start of the word (such as 'PN' = 'N', 'PH' = 'F').		:A variation of the SoundEx Algorithm. PhonetEx takes into account letter combinations that sound alike, particularly at the start of the word (such as 'PN' = 'N', 'PH' = 'F').

	===Returns===		===Returns===
	The Phonetex algorithm is a string transformation and comparison-based algorithm and is performed on the keybuilding. For example, JOHNSON would be transformed to "J565000000" and JHNSN would also be transformed to "J565000000" which would then be considered a Phonetex match after evaluation.		:The Phonetex algorithm is a string transformation and comparison-based algorithm and is performed on the keybuilding. For example, JOHNSON would be transformed to "J565000000" and JHNSN would also be transformed to "J565000000" which would then be considered a Phonetex match after evaluation.

	===Example Matchcode Component===		===Example Matchcode Component===
Line 19:		Line 19:
	{{ExampleDataTableV1\|STRING1\|STRING2\|RESULT		{{ExampleDataTableV1\|STRING1\|STRING2\|RESULT
	\|AdditionalRows=		\|AdditionalRows=
	{{EDTRow\|~~White~~\|Johnson\|Jhnsn\|Match Found}}		{{EDTRow\|Green\|Johnson\|Jhnsn\|Match Found}}
	{{EDTRow\|~~White~~\|Stephenz\|Stevens\|Match Found}}		{{EDTRow\|Green\|Stephenz\|Stevens\|Match Found}}
	{{EDTRow\|Green\|Beaumarchais\|Bumarchay\|Match Found}}		{{EDTRow\|Green\|Beaumarchais\|Bumarchay\|Match Found}}
	{{EDTRow\|Green\|Neumon\|Pneumon\|Match Found}}		{{EDTRow\|Green\|Neumon\|Pneumon\|Match Found}}
Line 34:		Line 34:

	===Recommended Usage===		===Recommended Usage===
	Large or enterprise level batch runs where. Using this algorithm will not prevent efficient clustering. Since the algorithm is performed during keybuilding, throughput will be fast.		:Large or enterprise level batch runs where. Using this algorithm will not prevent efficient clustering. Since the algorithm is performed during keybuilding, throughput will be fast.

	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.

	Databases of US and English language origin.		:Databases of US and English language origin.

	===Not Recommended For===		===Not Recommended For===
	Databases of non-US and non-English language origin.		:Databases of non-US and non-English language origin.

	Fields whose content data is of type Dictionary or Quantifiable.		:Fields whose content data is of type Dictionary or Quantifiable.

	===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]]

Admin at 23:46, 25 September 2018

2018-09-25T23:46:37Z

← Older revision		Revision as of 23:46, 25 September 2018
Line 14:		Line 14:

	===Example Matchcode Component===		===Example Matchcode Component===
	:[[File:~~MCO_Algorithm_Phontex~~.png\|link=]]		:[[File:MCO_Algorithm_Phonetex.png\|link=]]

	===Example Data===		===Example Data===

Admin: Created page with "{{MatchcodeOptimizationNav |AlgorithmsCollapse= }} ==Phonetex== ===Specifics=== (pronounced "Fo-NEH-tex") An auditory matching algorithm developed by Melissa Data. It works b..."

2018-09-25T23:46:26Z

Created page with "{{MatchcodeOptimizationNav |AlgorithmsCollapse= }} ==Phonetex== ===Specifics=== (pronounced "Fo-NEH-tex") An auditory matching algorithm developed by Melissa Data. It works b..."

New page

{{MatchcodeOptimizationNav
|AlgorithmsCollapse=
}}

==Phonetex==
===Specifics===
(pronounced "Fo-NEH-tex") An auditory matching algorithm developed by Melissa Data. It works best in matching words that sound alike but are spelled differently. It is an improvement over the Soundex algorithm.

===Summary===
A variation of the SoundEx Algorithm. PhonetEx takes into account letter combinations that sound alike, particularly at the start of the word (such as 'PN' = 'N', 'PH' = 'F').

===Returns===
The Phonetex algorithm is a string transformation and comparison-based algorithm and is performed on the keybuilding. For example, JOHNSON would be transformed to "J565000000" and JHNSN would also be transformed to "J565000000" which would then be considered a Phonetex match after evaluation.

===Example Matchcode Component===
:[[File:MCO_Algorithm_Phontex.png|link=]]

===Example Data===
{{ExampleDataTableV1|STRING1|STRING2|RESULT
|AdditionalRows=
{{EDTRow|White|Johnson|Jhnsn|Match Found}}
{{EDTRow|White|Stephenz|Stevens|Match Found}}
{{EDTRow|Green|Beaumarchais|Bumarchay|Match Found}}
{{EDTRow|Green|Neumon|Pneumon|Match Found}}
}}

{{MatchcodePerformance
|Performance4=
|Matches4=
}}

===Recommended Usage===
Large or enterprise level batch runs where. Using this algorithm will not prevent efficient clustering. Since the algorithm is performed during keybuilding, throughput will be fast.

Databases created via real-time data entry where audio likeness errors are introduced.

Databases of US and English language origin.

===Not Recommended For===
Databases of non-US and non-English language origin.

Fields whose content data is of type Dictionary or Quantifiable.

===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.

[[Category:MatchUp Hub]]
[[Category:Matchcode Optimization]]