Skip to content
/ lorca Public

Natural Language Processing for Spanish in Node.js. Stemmer, sentiment analysis, readability, tf-idf with batteries, concordance and more!

License

Notifications You must be signed in to change notification settings

dmarman/lorca

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

69 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

npm Packagist

Lorca.js

Lorca is a NLP library for Spanish written in javascript. Tokenization, concordance, stemmer, statistics, sentiment analysis, readability, tf-idf and more!

Installation

Client-side

Not supported yet, but soon.

Server-side

Run:

$ npm install lorca-nlp

Start using the library like:

const lorca = require('lorca-nlp');

var doc = lorca('esto es un test');

doc.words().get();
// [ 'esto', 'es', 'un', 'test' ]

API Concept

This library lets concatenate different methods to the document you are working on. Each time a method is executed, its output is stored in the doc object. If you need to execute methods more than once you have to make use of the load() method. This will reload the original document in the doc object.

var doc = lorca('En verano hace calor. En invierno hace frío');

// This stores the concordance output in the doc object.
var concordance = doc.concordance().sort().get();

// If you now need the words of your document, you must reload it with load().
var originalWords = doc.load().words().get();

Text tokenization

Extract sentences, words or syllables.

var doc = lorca('En verano hace calor. En invierno hace frío');

doc.get();
// En verano hace calor. En invierno hace frío.

doc.sentences().get();
// [ 'En verano hace calor.', ' En invierno hace frío.' ]

doc.words().get();
// [ 'en', 'verano', 'hace', 'calor', 'en', 'invierno', 'hace', 'frío' ]

doc.syllables().get();
// [ 'en', 've', 'ra', 'no', 'ha', 'ce', 'ca', 'lor.', 'en', 'in', 'vier', 'no', 'ha', 'ce','frí', 'o.' ]

doc.uniqueWords().get();
// [ 'en', 'verano', 'hace', 'calor', 'invierno', 'frío' ]

doc.onceWords().get();
// [ 'verano', 'calor', 'invierno', 'frío' ]

Group the output by sentence, word or both.

doc.sentences().words().get();
// [ [ 'en', 'verano', 'hace', 'calor' ],
//   [ 'en', 'invierno', 'hace', 'frío' ] ]

doc.sentences().words().syllables().get();
/*
 [ [ [ 'en' ],
     [ 've', 'ra', 'no' ],
     [ 'ha', 'ce' ],
     [ 'ca', 'lor' ] ],
   [ [ 'en' ],
     [ 'in', 'vier', 'no' ],
     [ 'ha', 'ce' ],
     [ 'frí', 'o' ] ] ]
*/

doc.sentences().syllables().get();
// [ [ 'En ', 've', 'ra', 'no', ' ha', 'ce ', 'ca', 'lor.' ],
//   [ ' En', ' in', 'vier', 'no', ' ha', 'ce ', 'frí', 'o.' ] ]

doc.words().syllables().get();
/*
[ [ 'en' ],
  [ 've', 'ra', 'no' ],
  [ 'ha', 'ce' ],
  [ 'ca', 'lor' ],
  [ 'en' ],
  [ 'in', 'vier', 'no' ],
  [ 'ha', 'ce' ],
  [ 'frí', 'o' ] ]
*/

Prepositions

Extract prepositions from text, sentences or words.

doc.prepositions().get();
// [ 'en', 'en' ]

doc.sentences().prepositions().get();
// [ [ 'en' ], [ 'en' ] ]

doc.words().prepositions().get();
// [ [ 'en' ], [], [], [], [ 'en' ], [], [], [] ]

Pronouns

Extract pronouns from text, sentences or words.

var doc = lorca('Yo le canto a él. Él se rie.');

doc.pronouns().get();
// [ 'yo', 'él', 'él' ]

doc.sentences().pronouns().get();
// [ [ 'yo', 'él' ], [ 'él' ] ]

doc.words().pronouns().get()
// [ [ 'yo' ], [], [], [], [ 'él' ], [ 'él' ], [], [] ]

doc.pronouns().percentage().get();
// 0.375

doc.sentences().pronouns().percentage().get();
// [ 0.4, 0.3333333333333333 ]

Adverbs

Extract adverbs from text, sentences or words.

var doc = lorca('En verano hace realmente calor. En invierno hace frío');

doc.adverbs().get();
// [ 'realmente' ]

doc.sentences().adverbs().get();
// [ [ 'realmente' ], [] ]

Passive Voice

Test whether a sentence is passive.

var doc = lorca('El niño ha sido castigado.');
doc.isPassive().get();
// true

var doc = lorca('El niño ha sido castigado. La madre lo ha castigado.');
doc.sentences().isPassive().get();
// [ true, false ]

Concordance

Get the word frequency of a document. The concordance method accepts the mode 'relative' which outputs the relative frequency of the words. It is posible to sort the output by frequency and to shorten the output array with the method sort().

var doc = lorca('En verano hace calor. En invierno hace frío');

doc.concordance().get();
// [ en: 2, verano: 1, hace: 2, calor: 1, invierno: 1, 'frío': 1 ]

doc.concordance().sort().get();
// [ en: 2, hace: 2, verano: 1, calor: 1, invierno: 1, 'frío': 1 ]

doc.concordance('relative').sort().get();
// [ en: 0.25, hace: 0.25, verano: 0.125 calor: 0.125, invierno: 0.125, 'frío': 0.125 ]

doc.concordance().sort(3).get();
// [ en: 2, hace: 2, verano: 1 ]

// Get the relative frequency from a huge corpus given by RAE.
doc.words().corpusFrequency().get();
// [ 0.02775516,
//   0.00008453,
//   0.00075057,
//   0.00007254,
//   0.02775516,
//   0.00004106,
//   0.00075057,
//   0.00007199 ]

doc.sentences().words().corpusFrequency().get();
// [ [ 0.02775516, 0.00008453, 0.00075057, 0.00007254 ],
// [ 0.02775516, 0.00004106, 0.00075057, 0.00007199 ] ]

Statistics

Get basic statistics of a text.

var doc = lorca('En verano hace calor. En invierno hace frío');

doc.words().get().length;
// 8

doc.sentences().get().length;
// 2

doc.wordsPerSentence().get();
// 4

doc.syllablesPerWord().get()
// 2

doc.syllablesPerSentence().get()
// 8

doc.uniqueWords().percentage().get();
// 0.75

doc.onceWords().percentage().get();
// 0.5

doc.prepositions().percentage().get();
// 0.25

doc.sentences().prepositions().percentage().get();
// [ 0.25, 0.25 ]

Readability

IFSZ Index

doc.ifsz().get();
// 78

doc.ifsz().grade().get();
// Bastante fácil

Sentiment

AFINN

Disclaimer: It uses a semi-automated translation of the original AFINN list. The list only contains words that are inside the 10.000 most used words. It has a total of 885 words. The sentiment() method calculates the relative value of each sentence and then it returns the relative values of those sentences. Positive values mean a positive sentiment and negative values mean negative sentiment.

The sentiment algorithm stems the text input in order to reach a wider spectrum of words.

var doc = lorca('El plátano está malo.');

doc.sentiment();
// -0.75

var doc = lorca('Me gusta la navidad.');

doc.sentiment();
// 0.5

var doc = lorca('El plátano está muy bueno. Me gusta la navidad. Esto no ha sido magnífico.');

doc.sentences().sentiment();
// [ 0.6, 0.5, -1.2 ]

doc.words().sentiment();
// [ 0, 0, 0, 0, 3, 0, 2, 0, 0, 0, -1, 0, 0, 5 ]

doc.sentences().words().sentiment()
// [ [ 0, 0, 0, 0, 3 ], [ 0, 2, 0, 0 ], [ 0, -1, 0, 0, 5 ] ]

doc.sentiment();
// -0.03333333333333329

ML-SENTICON

This method uses a powerful lemma-level lexicon created in 2014 by Fermín L. Cruz, José A. Troyano, Beatriz Pontes and F. Javier Ortega.

var doc = lorca('El plátano está malo.');

doc.sentiment('senticon');
// -0.09375

Stemmer

Get the stem of any word in Spanish. The stemmer is based on the Porter algorithm. You can also get the stemmed concordance of your document.

doc.stem('recomendaciones');
// recomend

var doc = lorca('Los niños juegan con las pelotas');
doc.words().stem().get();
// [ 'los', 'niñ', 'jueg', 'con', 'las', 'pelot' ]

var doc = lorca('Los niños juegan con las pelotas. Los profesores hablan del tiempo.');
doc.sentences().words().stem().get();
// [ [ 'los', 'niñ', 'jueg', 'con', 'las', 'pelot' ],
//   [ 'los', 'profesor', 'habl', 'del', 'tiemp' ] ]

var doc = lorca('Los niños juegan con las niñas.');
doc.words().stem().concordance().sort().get();
// { 'niñ': 2, los: 1, jueg: 1, con: 1, las: 1 }

tf-idf

The tf-idf has batteries included. It leverages a big frequency list to get the main words of any text.

var doc = lorca('En verano hace calor. En invierno hace frío. El verano me gusta');

doc.tfidf().sort().get();
// { verano: 4117.747963402167,
//   invierno: 2660.600722826124,
//   frío: 2192.690048750771,
//   calor: 2186.3476209394835,
//   gusta: 2068.4919519114765,
//   hace: 478.20393517589827,
//   me: -748.0756841870855,
//   el: -2833.037926222993,
//   en: -5539.036281420974 }

doc.tfidf().sort(2).get();
// { verano: 4117.747963402167,
//   invierno: 2660.600722826124 }

Reading Time

Get the reading time of a text in seconds. You can pass a reading speed as an argument in the readingtime(400) in words per minute. If no reading speed is given, it will use default value of 220 wpm.

var doc = lorca('El niño ha sido castigado. La madre lo ha castigado.');

doc.readingTime();
// 2.72

Search

Search any word in the text. You can use Regex too.

var doc = lorca('En verano hace calor. En invierno hace frío');

doc.find("verano");
// [ 'verano' ]

doc.sentences().find("verano");
// [ [ 'verano' ], [] ]

Testing

$ npm test

Thanks to

Vic - for his Spanish hyphenator in javascript. Cruz, Fermín L., José A. Troyano, Beatriz Pontes, F. Javier Ortega. Building layered, multilingual sentiment lexicons at synset and lemma levels, Expert Systems with Applications, 2014. For their senticon list in sentiment analysis.

About

Natural Language Processing for Spanish in Node.js. Stemmer, sentiment analysis, readability, tf-idf with batteries, concordance and more!

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published