Difference between revisions of "Global Name:Introduction"

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[[Global Name Web Service:Reference|← Global Name Web Service Reference]]
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! style="text-align:left; color:black; border-bottom:1px solid #aaaaaa;"|'''Global Name Web Service Navigation'''
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! style="color:black;"|[[Global Name Web Service:Introduction|Introduction]]
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|[[Global Name Web Service:Licensing|Licensing]]
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! style="color:black;"|[[Global Name Web Service:Request|Request]]
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|[[Global Name Web Service:Example Request|Example Request]]
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! style="color:black;"|[[Global Name Web Service:Response|Response]]
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! style="color:black;"|[[Global Name Web Service:Result Codes|Result Codes]]
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! style="color:black;"|[[Global Name Web Service:Sample Code|Sample Code]]
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Welcome to the Melissa Data Global Name Verification Service.
 
Global Name is able to parse, genderize, and standardize personal names as well as able to standardize company names. The service can screen out vulgar or obviously fake names.
Welcome to the Melissa Data Global Name Verification Web Service.
The Global Name Verification Web Service is able to parse, genderize, and standardize personal names as well as able to standardize company names. The service can screen out vulgar or obviously fake names.


*Parse full names into first, middle and last names, as well as prefixes like “Dr.” and suffixes like “Jr.”
*Parse full names into first, middle and last names, as well as prefixes like “Dr.” and suffixes like “Jr.”
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[[Category:Global Name Web Service]]
[[Category:Global Name]]
[[Category:Reference]]
[[Category:Reference]]

Revision as of 00:23, 10 March 2015

← Global Name

Global Name Navigation
Introduction
Licensing
Input/Request
Request Fields
Response Fields
Examples
REST JSON
REST JSONP
REST XML
Batch JSON
Batch SOAP
Batch XML
Result Codes
Result Code Use
Global Name Result Codes
Sample Code


Welcome to the Melissa Data Global Name Verification Service. Global Name is able to parse, genderize, and standardize personal names as well as able to standardize company names. The service can screen out vulgar or obviously fake names.

  • Parse full names into first, middle and last names, as well as prefixes like “Dr.” and suffixes like “Jr.”
  • Handle name strings that include two names, such as “John and Mary Jones.”
  • Correct misspelled first names
  • Flag vulgar and obviously fake names, such as “Bugs Bunny.”
  • Assign gender based on the first name
  • Standardize company names