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  NetGender for .NET Component Managed Code  
           
 

NetGender for .NET allows you to quickly and easily build Name Verification, Parsing and Gender Determination into your custom applications. Accurately verify whether a particular field contains a valid individual or company. NetGender uses a 100,000 name, ethnically diverse, dictionary in combination with an 8,000 word company dictionary to ensure precise gender determination.

 

  Name Verification - Quickly Identify Incomplete or incorrect names.

 

  Name Standardization - Prefixes and suffixes are abbreviated and standardized to your specifications.

 
 

  Name Parsing - Easily separate dual names in the same field including hyphenated last names.

 

  Gender Determination - 100,000 name, multi-ethnic dictionary for pinpoint accuracy.

 
  Vista Compatible        
     
 

$399 Single Developer License   Download Evaluation (8.96 MB)

$799 5 Developer Team License User's Guide

$1999 Site License - Unlimited Developers View Cart
      .NET Bundle Pricing      
 
     
  A Closer Look How NetGender Works    
         
 

NetGender for .NET accepts free-form names and then automatically splits them into standard components: Prefix, First, Middle, Last and Suffix no matter what the original format. Next, using a 100,000 Name Dictionary in combination with an 8,000 word proprietary Company Dictionary, the gender is determined with unmatched accuracy. For special cases, such as an all-girl school, you can easily override the built-in system dictionaries.

NetGender can process all styles of names including inverse, natural order, hyphenated and multi-part last names. Multiple names in the same field and companies can be easily separated providing you with powerful formatting control.

As a bonus, when you combine NetGender with our NetAddress product, you can even tackle the impossible task of identifying data that has been entered free-form. The names, addresses and C/S/Z either “float” from field to field or you are just not sure what's in the field. First, examine the Address_Quality flag returned from NetAddress. If set to High or Medium, it's almost certainly an address. If set to Low, submit the string to NetGender for name verification. Using these techniques you’ll always be certain of the data you're working with.

 

NetGender for .NET starts by carefully identifying each individual name element based on the Name_Style you’ve selected.  Intuitive algorithms examine the results and a selection is made of the most complete and correct data. Next, the name elements are split into their standard components and the user-specified prefix/suffix abbreviations are applied. Using a 100,000-Name Dictionary in conjunction with the pre-programmed rules from the 8,000 word Company Dictionary the correct gender is determined with pinpoint accuracy. The Name_Quality flag is then set to indicate how complete and correct the name is. Finally, the standardized name components are returned to your application along with a complete and cleansed composite name.

Not all gender identification systems are created the same. Most use a simple table of about 8,000 to 18,000 first names. NetGender uses an extensive 100,000 Name Dictionary that was specifically created with a rich ethnic diversity. This unique and powerful strategy produces results unmatched by any other software.

NetGender is the only name verification and parsing software that can reliably extract a name when the format of the name is variable or unknown.

 
         
         
   
Name_In MR DE LA ROSA, JUAN R OR MARIA
Name_Out Male Mr Juan R De La Rosa
Name2_Out Female Maria De La Rosa
Name_In SMITH-LA BELLA JR, JOHN A & MARY B, PHD
Name_Out Male John A Smith-La Bella Jr
Name2_Out Female Mary B Smith-La Bella PhD
Name_In MS MARY MYTH C/O THE SOFTWARE COMPANY
Name_Out Female Ms Mary Myth
Name2_Out Company The Software Company
Name_In O’LEARY-VAN HORN, DALE & MIKE
Name_Out Neutral Dale O’Leary-Van Horn
Name2_Out Male Mike O’Leary-Van Horn
Name_In MR J JONES & WIFE MAY
Name_Out Male Mr J Jones
Name2_Out Female May Jones
 
  The screen shot above was taken from a sample application created using VB.NET. Other samples, including C#, can be found in the NetGender folder.   NetGender's precise results are driven by a specially encoded, 100,000-name dictionary that was specifically created with a rich ethnic diversity.  
         
  Benefits Features    
         
  Identify Gender Makeup of Your List for Target Marketing Prefixes and Suffixes are Standardized to Your Specifications
  Nicknames Property - Invaluable for Finding Duplicate Names Proper Case Conversion for More Attractive Data Presentation
  User Updatable Tables So Your Applications Never Go Out-of-Date Royalty Free Run-Time (License Agreement)
  Set Proper Salutations for a More Personalized List Parse Full Names Into 5 Separate Components
  FREE Upgrades for a Full Year (Maintenance Agreement) Designed for use with all .NET Compatible Programming Languages
         
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