# metaparse
This is to be a machine learning project to extract metainformation about information sources, such as agents online that share information.
## Problem specification
Given some data from an information source I, recognize its [intent about content](https://wefindx.net) towards the world, answering following questions about the information source and its information content:
F(domain).assets:
.Agent (who?)
.Place (where?)
.Event (when?)
.Topic (about what?)
X(process).actions:
. doing (doing what?)
Y(range).targets:
.Goal (why?)
.Idea (how in principle?)
.Plan (what specifically?)
.Step (in what order?)
This will allow to treat every information source as an instance of equation optimization process F(X)=Y, where the actions of agents are explained by their intents (Y) about content their world model (F).
Metadata
Release files for metaparse 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| metaparse-0.0.1.tar.gz | 1.6 kB | Details |
Release files / metaparse-0.0.1.tar.gz
| Download URL | metaparse-0.0.1.tar.gz |
|---|---|
| Size | 1.6 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
cc5d164923cbc7b987f2d06742012ef8d0b29f45043911249c3894d74c9e3d89
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BLAKE2b-256 checksum How to use checksums |
165c5838fc6ac18c4ffcdb4bb06f2fd7c04f6cdfcd8de1efe28e9441521a728f
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No |
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Python-urllib/3.7
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