Difference between revisions of "DSL generator"

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==Approach==
 
==Approach==
The most important data want to capture is the companies' tags, the images' tag, companies' short description, and companies' long description. For example, if we look at  
+
The most important data we want to capture is the companies' tags, the images' tags, companies' short description, and companies' long description. For example, if we look at  
 
  view-source:https://www.boost.vc/companies/
 
  view-source:https://www.boost.vc/companies/
  
We want to capture the tag that is associated with the companies' logos, the names of companies, the short descriptions of companies, and companies websites. The goal is to compress all of those into one DSL so that our [model http://www.edegan.com/wiki/DSL_Encoding] could learn the structure that we want.
+
We want to capture the tags that are associated with the companies' logos, the names of companies, the short descriptions of companies, and companies websites. The goal is to compress all of those into one DSL so that our [model http://www.edegan.com/wiki/DSL_Encoding] could learn the structure that we want.
  
 
This [https://metacpan.org/pod/DSL::HTML::Compiler article] can be a good start to look at
 
This [https://metacpan.org/pod/DSL::HTML::Compiler article] can be a good start to look at

Revision as of 11:13, 30 May 2019


Project
DSL generator
Project logo 02.png
Project Information
Has title DSL Geneator
Has owner Hiep Nguyen
Has start date 2019/05/16
Has deadline date
Has project status Active
Copyright © 2019 edegan.com. All Rights Reserved.


Approach

The most important data we want to capture is the companies' tags, the images' tags, companies' short description, and companies' long description. For example, if we look at

view-source:https://www.boost.vc/companies/

We want to capture the tags that are associated with the companies' logos, the names of companies, the short descriptions of companies, and companies websites. The goal is to compress all of those into one DSL so that our [model http://www.edegan.com/wiki/DSL_Encoding] could learn the structure that we want.

This article can be a good start to look at