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nlp-toolkit
Advanced tools
This module covers some basic nlp principles and implementations. Every implementation in this module is written as stream to only hold that data in memory that is currently processed at any step.
This module covers some basic nlp principles and implementations. The main focus is performance. When we deal with sample or training data in nlp, we quickly run out of memory. Therefore every implementation in this module is written as stream to only hold that data in memory that is currently processed at any step.
npm install nlp-toolkit
Frequency distribution of words in texts. Tokenize, remove stopwords, stem words, count words. Traditionally those steps happen sequentially. But we do not need to tokenize the whole text before removing stopwords.
var nlp = require('nlp-toolkit');
var fs = require('fs');
var es = require('event-stream');
fs.createReadStream('./pride_prejudice.txt')
.pipe(es.split())
.pipe(nlp.tokenizer())
.pipe(nlp.stopwords())
.pipe(nlp.stemmer())
.pipe(nlp.frequency())
.on('data', function (freqDist) {
console.log(freqDist.slice(0, 10));
})
.on('error', function (err) {
console.error(err);
});
.pipe(nlp.tokenizer(options))
options
:
attribute | type | description |
---|---|---|
characters | RegExp | regular expression that describes what characters to strip of off (default /[^\w]/g ). |
separator | RegExp | regular expression that describes where to split words (default /\s/g ). |
eliminateNumbers | boolean | discard tokens that only contain numbers (default false ). |
toLowerCase | boolean | transform every token to lower case (default true ). |
emptyStrings | boolean | keep empty string when through some previous steps tokens result in length === 0 (default false ). |
Tokenizer also work in a non-stream context:
var tokens = nlp.tokenizer(string, options);
.pipe(nlp.stopwords(options))
options
:
attribute | type | description |
---|---|---|
defaultLang | string | default language if processed object does not provide a lang attribute (default en ). |
additionalWords | object | add additional stopwords to the list of stopwords |
additionalWords
:
attribute | type | description |
---|---|---|
all | array | list of stopwords to add to every language |
default | array | list of stopwords if language is not supported |
lang | array | list of stopwords specific to lang |
Supported languages: da, de, en, es, fi, fr, hu, it, nl, no, pt, ro, ru, se, tr
.
Stopwords also work in a non-stream context:
nlp.stopwords(sentence, options)
.then(function (tokens) {}})
.catch(function (err) { console.error(err); });
.pipe(nlp.stemmer(options))
options
:
attribute | type | description |
---|---|---|
defaultStemmer | string | default stemmer for language if processed object does not provide a lang attribute (default en ). |
Supported languages: da, de, en, es, fi, fr, hu, it, nl, no, pt, ro, ru, se, tr
.
Stopwords also work in a non-stream context:
var tokens = nlp.stemmer(sentence, options);
This module uses the stemmer implementation of Snowball-Stemmer.
.pipe(nlp.frequency())
FAQs
This module covers some basic nlp principles and implementations. Every implementation in this module is written as stream to only hold that data in memory that is currently processed at any step.
We found that nlp-toolkit 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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