Orange3 TextMining add-on.
Project description
Orange3 Text
Orange add-on for text mining. It provides access to publicly available data, like NY Times, Twitter and PubMed. Further, it provides tools for preprocessing, constructing vector spaces (like bag-of-words, topic modeling and word2vec) and visualizations like word cloud end geo map. All features can be combined with powerful data mining techniques from the Orange data mining framework.
See documentation.
Features
Access to data
- Load a corpus of text documents
- Access publicly available data (The Guardian, NY Times, Twitter, Wikipedia, PubMed)
Text analysis
- Preprocess corpus
- Generate bag of words
- Embed documents into vector space
- Perform sentiment analysis
- Detect emotions in tweets
- Discover topics in the text
- Compute document statistics
- Visualize frequent words in the word cloud
- Find words that enrich selected documents
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| Filename, size | File type | Python version | Upload date | Hashes |
|---|---|---|---|---|
| Filename, size Orange3_Text-1.5.1-py3-none-any.whl (34.2 MB) | File type Wheel | Python version py3 | Upload date | Hashes View |
| Filename, size Orange3-Text-1.5.1.tar.gz (41.3 MB) | File type Source | Python version None | Upload date | Hashes View |
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