simple_keyword_clusterer
A simple machine learning package to cluster keywords in higher-level groups. (by andrea-dagostino)
KeyBERT
Minimal keyword extraction with BERT (by MaartenGr)
| simple_keyword_clusterer | KeyBERT | |
|---|---|---|
| 2 | 5 | |
| 15 | 3,217 | |
| - | - | |
| 0.0 | 6.1 | |
| almost 2 years ago | about 1 month ago | |
| Python | Python | |
| 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.
simple_keyword_clusterer
Posts with mentions or reviews of simple_keyword_clusterer.
We have used some of these posts to build our list of alternatives
and similar projects.
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?
What are some alternatives?
When comparing simple_keyword_clusterer and KeyBERT you can also consider the following projects:
yake - Single-document unsupervised keyword extraction
rake-nltk - Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.
RAKE-tutorial - A python implementation of the Rapid Automatic Keyword Extraction
flashtext - Extract Keywords from sentence or Replace keywords in sentences.
pke - Python Keyphrase Extraction module
faiss - A library for efficient similarity search and clustering of dense vectors.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
scattertext - Beautiful visualizations of how language differs among document types.
phrasemachine - Quickly extract multi-word phrases from a corpus
pyate - PYthon Automated Term Extraction