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rapid-automated-keyword-extraction
Advanced tools
An javascript implementation of the Rapid Automated Keyword Extraction (RAKE) algorithm
The goal of this library was to create a well tested Javascript translation of the python implementation.
Differences in regular expressions and stopword lists have big impacts on this algorithm and sticking close to the python means that the code was easy to compare to ensure that it was in the ballpark.
This algorithm is described in Text Mining: Applications and Theory and also in this excellent blog post by Alyona Medelyan.
It operates using only the text you give it and produces surprisingly good results. There are likely better results possible but these mostly seem to involve a combination of Python, Machine Learning and a corpus of data.
The appeal of RAKE is of the "bang for the buck" variety.
Currently this library produces subtly different results than either the paper or the original Python implementation. While the results (especially the top scoring ones) line up nicely, these little deviations represent something to understand and resolve.
npm i rapid-automated-keyword-extraction
> var rake = require('rapid-automated-keyword-extraction').default
undefined
> rake('Compatibility of systems of linear constraints over the set of natural numbers', 'test/data/salton_1971_smartstoplist.txt').then(console.log)
{ 'natural numbers': 4,
'linear constraints': 4,
set: 1,
systems: 1,
compatibility: 1 }
The stopword list used by the python version is here. It has a comment as the first line which might break the world...
Links to other stopword lists can be found here
Any file with one word per line should be fine.
After hammering out differences in the results, plans are to focus on
FAQs
An javascript implementation of the Rapid Automated Keyword Extraction (RAKE) algorithm
The npm package rapid-automated-keyword-extraction receives a total of 12 weekly downloads. As such, rapid-automated-keyword-extraction popularity was classified as not popular.
We found that rapid-automated-keyword-extraction demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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