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[UNMAINTAINED] Extract terms and keywords from a piece of text
Branch: master


glossary is a JavaScript module that extracts keywords from text (aka "term extraction" or "auto tagging"). It takes a string of text and returns an array of terms that are relevant to the content:

var glossary = require("glossary");

var keywords = glossary.extract("Her cake shop is the best in the business");

console.log(keywords)  // ["cake", "shop", "cake shop", "business"]

glossary is standalone and uses part-of-speech analysis to extract the relevant terms.


For node with npm:

npm install glossary



Use blacklist to remove unwanted terms from any extraction:

var glossary = require("glossary")({
   blacklist: ["library", "script", "api", "function"]

var keywords = glossary.extract("JavaScript color conversion library");

console.log(keywords); // ["color", "conversion"]

minimum frequency

Use minFreq to limit the terms to only those that occur with a certain frequency:

var glossary = require("glossary")({ minFreq: 2 });

var keywords = glossary.extract("Kasey's pears are the best pears in Canada");

console.log(keywords); // ["pears"]


Use collapse to remove terms that are sub-terms of other terms:

var glossary = require("glossary")({ collapse: true });

var keywords = glossary.extract("The Middle East crisis is getting worse");

console.log(keywords); // ["Middle East crisis"]

verbose output

Use verbose to also get the count of each term:

var glossary = require("glossary")({ verbose: true });

var keywords = glossary.extract("The pears from the farm are good");

console.log(keywords); // [ { word: 'pears', count: 1 }, { word: 'farm', count: 1 } ]


glossary Uses jspos for POS tagging. It's inspired by the python module topia.termextract.

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