KeyBERT
Minimal keyword extraction with BERT (by MaartenGr)
pyate
PYthon Automated Term Extraction (by kevinlu1248)
| KeyBERT | pyate | |
|---|---|---|
| 5 | 1 | |
| 3,217 | 283 | |
| - | - | |
| 6.1 | 0.0 | |
| about 2 months ago | about 1 year ago | |
| Python | HTML | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
KeyBERT
Posts with mentions or reviews of KeyBERT.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-28.
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I want to extract important keywords from large documents...
Use something else like KeyBERT or BERTopic: https://github.com/MaartenGr/KeyBERT It's much faster.
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[D]: Predict the most probable document including the answer to a given question
Using keyword similarity using KeyBERT:https://github.com/MaartenGr/KeyBERT (i.e. loading keywords for each of the given documents and compare to the keywords of the question)
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BERT execution time
Would anyone know an equation or a general rule of thumb for how long it would take this BERT algorithm (KeyBERT: https://github.com/MaartenGr/KeyBERT) to select n keywords from a string of character length m on a GPU of certain relevant specs?
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[P] Building model to extract keywords from legal documents
Look into rake, pke, phrasemachine, pyate, keybert.
- Alternate approaches to TF-IDF?
pyate
Posts with mentions or reviews of pyate.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-24.
-
[P] Building model to extract keywords from legal documents
Look into rake, pke, phrasemachine, pyate, keybert.
What are some alternatives?
When comparing KeyBERT and pyate you can also consider the following projects:
yake - Single-document unsupervised keyword extraction
pke - Python Keyphrase Extraction module
RAKE-tutorial - A python implementation of the Rapid Automatic Keyword Extraction
datefinder - Find dates inside text using Python and get back datetime objects
flashtext - Extract Keywords from sentence or Replace keywords in sentences.
phrasemachine - Quickly extract multi-word phrases from a corpus
faiss - A library for efficient similarity search and clustering of dense vectors.
speaking_with_plato - Exploring Plato's philosophy with AI - A Data Spiral blog article
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
scattertext - Beautiful visualizations of how language differs among document types.