.. Copyright (C) 2001-2018 NLTK Project .. For license information, see LICENSE.TXT ========== Stemmers ========== Overview ~~~~~~~~ Stemmers remove morphological affixes from words, leaving only the word stem. >>> from __future__ import print_function >>> from nltk.stem import * Unit tests for the Porter stemmer ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ >>> from nltk.stem.porter import * Create a new Porter stemmer. >>> stemmer = PorterStemmer() Test the stemmer on various pluralised words. >>> plurals = ['caresses', 'flies', 'dies', 'mules', 'denied', ... 'died', 'agreed', 'owned', 'humbled', 'sized', ... 'meeting', 'stating', 'siezing', 'itemization', ... 'sensational', 'traditional', 'reference', 'colonizer', ... 'plotted'] >>> singles = [stemmer.stem(plural) for plural in plurals] >>> print(' '.join(singles)) # doctest: +NORMALIZE_WHITESPACE caress fli die mule deni die agre own humbl size meet state siez item sensat tradit refer colon plot Unit tests for Snowball stemmer ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ >>> from nltk.stem.snowball import SnowballStemmer See which languages are supported. >>> print(" ".join(SnowballStemmer.languages)) arabic danish dutch english finnish french german hungarian italian norwegian porter portuguese romanian russian spanish swedish Create a new instance of a language specific subclass. >>> stemmer = SnowballStemmer("english") Stem a word. >>> print(stemmer.stem("running")) run Decide not to stem stopwords. >>> stemmer2 = SnowballStemmer("english", ignore_stopwords=True) >>> print(stemmer.stem("having")) have >>> print(stemmer2.stem("having")) having The 'english' stemmer is better than the original 'porter' stemmer. >>> print(SnowballStemmer("english").stem("generously")) generous >>> print(SnowballStemmer("porter").stem("generously")) gener .. note:: Extra stemmer tests can be found in `nltk.test.unit.test_stem`.