Difference between revisions of "DSL generator"
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{{Project | {{Project | ||
| + | |Has project output=Tool | ||
| + | |Has sponsor=Kauffman Incubator Project | ||
|Has title=DSL Geneator | |Has title=DSL Geneator | ||
|Has owner=Hiep Nguyen | |Has owner=Hiep Nguyen | ||
| Line 7: | Line 9: | ||
==Approach== | ==Approach== | ||
| − | The most important data want to capture is the companies' tags, the images' | + | 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 | + | 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 | ||
Latest revision as of 12:47, 21 September 2020
| DSL generator | |
|---|---|
| Project Information | |
| Has title | DSL Geneator |
| Has owner | Hiep Nguyen |
| Has start date | 2019/05/16 |
| Has deadline date | |
| Has project status | Active |
| Has sponsor | Kauffman Incubator Project |
| Has project output | Tool |
| 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
