This project has been transfered to NaturalNode/natural, please follow it there.
"Natural" is a general natural language facility for nodejs. Stemming, classification, phonetics, WordNet, and some inflection are currently supported.
It's still in the early stages, and am very interested in bug reports, contributions and the like.
At the moment most algorithms are English-specific but long-term some diversity is in order.
Aside from this README the only current documentation is here on my blog.
If you're just looking to consume natural without your own node application please install the NPM
npm install natural
If you're interested in contributing to natural or just hacking it then by all means fork away!
Currently stemming is supported via the Porter and Lancaster (Paice/Husk) algorithms.
var natural = require('natural');
this example uses a porter stemmer. "word" is returned.
console.log(natural.PorterStemmer.stem("words")); // stem a single word
attach() patches stem() and tokenizeAndStem() to String as a shortcut to PorterStemmer.stem(token). tokenizeAndStem() breaks text up into single words and returns an array of stemmed tokens.
natural.PorterStemmer.attach();
console.log("i am waking up to the sounds of chainsaws".tokenizeAndStem());
console.log("chainsaws".stem());
the same thing can be done with a lancaster stemmer
natural.LancasterStemmer.attach();
console.log("i am waking up to the sounds of chainsaws".tokenizeAndStem());
console.log("chainsaws".stem());
var natural = require('natural'),
classifier = new natural.BayesClassifier();
you can train the classifier on sample text. it will use reasonable defaults to tokenize and stem the text.
classifier.train([{classification: 'buy', text: "i am long qqqq"},
{classification: 'buy', text: "buy the q's"},
{classification: 'sell', text: "short gold"},
{classification: 'sell', text: "sell gold"}
]);
outputs "sell"
console.log(classifier.classify('i am short silver'));
outputs "buy"
console.log(classifier.classify('i am long copper'));
classifier = new natural.BayesClassifier();
the classifier can also be trained on and classify arrays of tokens, strings, or any mixture. arrays let you use entirely custom data with your own tokenization/stemming if any at all.
classifier.train([{classification: 'hockey', text: ['puck', 'shoot']},
{classification: 'hockey', text: 'goalies stop pucks.'},
{classification: 'stocks', text: ['stop', 'loss']},
{classification: 'stocks', text: 'creat a stop order'}
]);
console.log(classifier.classify('stop out at $100'));
console.log(classifier.classify('stop the puck, fool!'));
console.log(classifier.classify(['stop', 'out']));
console.log(classifier.classify(['stop', 'puck', 'fool']));
A classifier can also be persisted and recalled so you can reuse a training.
var classifier = new natural.BayesClassifier();
classifier.train([{classification: 'buy', text: ['long', 'qqqq']},
{classification: 'buy', text: "buy the q's"},
{classification: 'sell', text: "short gold"},
{classification: 'sell', text: ['sell', 'gold']}
]);
persist to a file on disk named "classifier.json"
classifier.save('classifier.json', function(err, classifier) {
// the classifier is saved to the classifier.json file!
});
and to recall from the classifier.json saved above:
natural.BayesClassifier.load('classifier.json', function(err, classifier) {
console.log(classifier.classify('long SUNW'));
console.log(classifier.classify('short SUNW'));
});
A classifier can also be serialized and deserialized as such
var classifier = new natural.BayesClassifier();
classifier.train([{classification: 'buy', text: ['long', 'qqqq']},
{classification: 'buy', text: "buy the q's"},
{classification: 'sell', text: "short gold"},
{classification: 'sell', text: ['sell', 'gold']}
]);
// serialize
var raw = JSON.stringify(classifier);
// deserialize
var restoredClassifier = natural.BayesClassifier.restore(raw);
console.log(restoredClassifier.classify('i am short silver'));
console.log(restoredClassifier.classify('i am long silver'));
Phonetic matching (sounds-like) matching can be done with either the SoundEx or Metaphone algorithms
var natural = require('natural'),
metaphone = natural.Metaphone, soundEx = natural.SoundEx;
var wordA = 'phonetics';
var wordB = 'fonetix';
test the two words to see if they sound alike
if(metaphone.compare(wordA, wordB))
console.log('they sound alike!');
the raw phonetics are obtained with process()
console.log(metaphone.process('phonetics'));
attaching will patch String with useful methods
metaphone.attach();
soundsLike is essentially a shortcut to Metaphone.compare
if(wordA.soundsLike(wordB))
console.log('they sound alike!');
the raw phonetics are obtained with phonetics()
console.log('phonetics'.phonetics());
full text strings can be tokenized into arrays of phonetics similar to stemmers
console.log('phonetics rock'.tokenizeAndPhoneticize());
same module operations apply with SoundEx
if(soundEx.compare(wordA, wordB))
console.log('they sound alike!');
console.log(soundEx.process('phonetics'));
the same String patches apply with soundex
soundEx.attach();
if(wordA.soundsLike(wordB))
console.log('they sound alike!');
console.log('phonetics'.phonetics());
Nouns can be pluralized/singularized with a NounInflector
var natural = require('natural'),
nounInflector = new natural.NounInflector();
to pluralize a word (outputs "radii")
console.log(nounInflector.pluralize('radius'));
to singularize a word (outputs "beer")
console.log(nounInflector.singularize('beers'));
Like many of the other features String can be patched to perform the operations directly. The "Noun" suffix to the methods is necessary as verbs will be supported in the future.
nounInflector.attach();
console.log('radius'.pluralizeNoun());
console.log('beers'.singularizeNoun());
Numbers can be counted with a CountInflector
var countInflector = natural.CountInflector;
outputs "1st"
console.log(countInflector.nth(1));
outputs "111th"
console.log(countInflector.nth(111));
Present Tense Verbs can be pluralized/singularized with a PresentVerbInflector. This feature is still experimental as of 0.0.42 so use with caution and please provide feedback.
var verbInflector = new natural.PresentVerbInflector();
outputs "becomes"
console.log(verbInflector.singularize('become'));
outputs "become"
console.log(verbInflector.pluralize('becomes'));
Like many other natural modules attach() can be used to patch strings with handy methods.
verbInflector.attach();
console.log('walk'.singularizePresentVerb());
console.log('walks'.pluralizePresentVerb());
One of the newest and most experimental features is WordNet integration. Here's an example of using natural to look up definitions of the word node. The parameter in the WordNet constructor is the local directory that will store the WordNet database files. If the database files are not present in the specified directories natural will download them for you.
Keep in mind the WordNet integration is to be considered experimental at this point and not production ready. The API is also subject to change.
Here's an exmple of looking up definitions for the word, "node".
var wordnet = new natural.WordNet('.');
wordnet.lookup('node', function(results) {
results.forEach(function(result) {
console.log('------------------------------------');
console.log(result.synsetOffset);
console.log(result.pos);
console.log(result.lemma);
console.log(result.pos);
console.log(result.gloss);
});
});
Given a synset offset and part of speech a definition can be looked up directly.
var wordnet = new natural.WordNet('.');
wordnet.get(4424418, 'n', function(result) {
console.log('------------------------------------');
console.log(result.lemma);
console.log(result.pos);
console.log(result.gloss);
});
You can also lookup synonyms for all meanings of a word.
var wordnet = new natural.WordNet('.');
wordnet.lookupSynonyms('device', function(results) {
results.forEach(function(result) {
console.log('------------------------------------');
console.log(result.synsetOffset);
console.log(result.pos);
console.log(result.lemma);
console.log(result.pos);
console.log(result.gloss);
});
});
It's also possible to lookup synonyms for a single meaning.
var wordnet = new natural.WordNet('.');
wordnet.lookup('entity', function(results) {
wordnet.getSynonyms(results[0], function(results) {
results.forEach(function(result) {
console.log('------------------------------------');
console.log(result.synsetOffset);
console.log(result.pos);
console.log(result.lemma);
console.log(result.pos);
console.log(result.gloss);
});
});
});
Note that getSynonyms supports query by offset and part of speech.
var wordnet = new natural.WordNet('.');
wordnet.getSynonyms(4424418, 'n', function(results) {
results.forEach(function(result) {
console.log('------------------------------------');
console.log(result.lemma);
console.log(result.pos);
console.log(result.gloss);
});
});
Princeton University "About WordNet." WordNet. Princeton University. 2010. http://wordnet.princeton.edu
Copyright (c) 2011, Chris Umbel
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