pytextrank
pke

pytextrank | pke | |
---|---|---|
2 | 3 | |
2,166 | 1,570 | |
0.3% | - | |
4.7 | 3.1 | |
7 months ago | over 1 year ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 only |
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pytextrank
pke
- Question on easing comprehension
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[P] Building model to extract keywords from legal documents
Look into rake, pke, phrasemachine, pyate, keybert.
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Best approach for automatic key word extraction
There are lots of off-the-shelf tools for this. Look into: - https://github.com/boudinfl/pke - https://github.com/kevinlu1248/pyate - https://github.com/zelandiya/RAKE-tutorial - https://github.com/slanglab/phrasemachine - https://github.com/MaartenGr/KeyBERT/
What are some alternatives?
turing - :sparkles: :dna: Turing ES - Enterprise Search, Chatbot using Search Engine and Many NLP Vendors.
KeyBERT - Minimal keyword extraction with BERT
Text-Summarization-using-NLP - Text Summarization using NLP to fetch BBC News Article and summarize its text and also it includes custom article Summarization
textstat - :memo: python package to calculate readability statistics of a text object - paragraphs, sentences, articles.
retext-readability - plugin to check readability
rake-nltk - Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.
zsl-kg - Framework for zero-shot learning with knowledge graphs.
phrasemachine - Quickly extract multi-word phrases from a corpus
spacy-models - 💫 Models for the spaCy Natural Language Processing (NLP) library
yake - Single-document unsupervised keyword extraction
