Cortical.io’s Retina API allows the user to perform semantic operations on text. One can for example:
measure the semantic similarity between two written entities
create a semantic classifier based on positive and negative example texts
extract keywords from a text
divide a text into sub-sections corresponding to semantic changes
extract terms from a text based on part of speech tags
The meaning of terms and texts is stored in a sparse binary representation that allows the user to apply logical operators to refine the semantic representation of a concept.
You can read more about the technology at the documentation page.
To access the API, you will need to register for an API key.
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Release files for retinasdk 1.0.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| retinasdk-1.0.0.tar.gz | 8.9 kB | Without provenance | Details for retinasdk-1.0.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| retinasdk-1.0.0-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details for retinasdk-1.0.0-py2.py3-none-any.whl |
Total release size: 30.7 kB
Release files / retinasdk-1.0.0.tar.gz
| Download URL | retinasdk-1.0.0.tar.gz |
|---|---|
| Size | 8.9 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / retinasdk-1.0.0-py2.py3-none-any.whl
| Download URL | retinasdk-1.0.0-py2.py3-none-any.whl |
|---|---|
| Size | 21.8 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for retinasdk 1.0.0
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