UNPKG

natural

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General natural language (tokenizing, stemming (English, Russian, Spanish), part-of-speech tagging, sentiment analysis, classification, inflection, phonetics, tfidf, WordNet, jaro-winkler, Levenshtein distance, Dice's Coefficient) facilities for node.

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/* Copyright (c) 2012, Guillaume Marty Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ 'use strict' /** * A very basic stemmer that performs the following steps: * * Stem katakana. * Inspired by: * http://svn.apache.org/repos/asf/lucene/dev/trunk/lucene/analysis/kuromoji/src/java/org/apache/lucene/analysis/ja/JapaneseKatakanaStemFilter.java * * This script assumes input is normalized using normalizer_ja(). * * \@todo Use .bind() in StemmerJa.prototype.attach(). */ const Tokenizer = require('../tokenizers/tokenizer_ja') const stopwords = require('../util/stopwords_ja').words /** * @constructor */ const StemmerJa = function () { } /** * Tokenize and stem a text. * Stop words are excluded except if the second argument is true. * * @param {string} text * @param {boolean} keepStops Whether to keep stop words from the output or not. * @return {Array.<string>} */ StemmerJa.prototype.tokenizeAndStem = function (text, keepStops) { const self = this const stemmedTokens = [] const tokens = new Tokenizer().tokenize(text) // This is probably faster than an if at each iteration. if (keepStops) { tokens.forEach(function (token) { let resultToken = token.toLowerCase() resultToken = self.stem(resultToken) stemmedTokens.push(resultToken) }) } else { tokens.forEach(function (token) { if (stopwords.indexOf(token) === -1) { let resultToken = token.toLowerCase() resultToken = self.stem(resultToken) stemmedTokens.push(resultToken) } }) } return stemmedTokens } /** * Stem a term. * * @param {string} token * @return {string} */ StemmerJa.prototype.stem = function (token) { token = this.stemKatakana(token) return token } /** * Remove the final prolonged sound mark on katakana if length is superior to * a threshold. * * @param {string} token A katakana string to stem. * @return {string} A katakana string stemmed. */ StemmerJa.prototype.stemKatakana = function (token) { const HIRAGANA_KATAKANA_PROLONGED_SOUND_MARK = 'ー' const DEFAULT_MINIMUM_LENGTH = 4 if (token.length >= DEFAULT_MINIMUM_LENGTH && token.slice(-1) === HIRAGANA_KATAKANA_PROLONGED_SOUND_MARK && this.isKatakana(token)) { token = token.slice(0, token.length - 1) } return token } /** * Is a string made of fullwidth katakana only? * This implementation is the fastest I know: * http://jsperf.com/string-contain-katakana-only/2 * * @param {string} str A string. * @return {boolean} True if the string has katakana only. */ StemmerJa.prototype.isKatakana = function (str) { return !!str.match(/^[゠-ヿ]+$/) } /* // Expose an attach function that will patch String with new methods. StemmerJa.prototype.attach = function () { const self = this String.prototype.stem = function () { return self.stem(this) } String.prototype.tokenizeAndStem = function (keepStops) { return self.tokenizeAndStem(this, keepStops) } } */ module.exports = new StemmerJa()