Python Stemming and Lemmatization
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2023-12-01
在自然语言处理领域,我们遇到两个或多个单词具有共同根的情况。 例如,三个词 - 同意,同意和同意具有相同的词根同意。 涉及任何这些词的搜索应将它们视为同一个词,即根词。 因此,将所有单词链接到根词中变得至关重要。 NLTK库具有执行此链接的方法,并提供显示根词的输出。
以下程序使用Porter Stemming算法进行词干分析。
import nltk
from nltk.stem.porter import PorterStemmer
porter_stemmer = PorterStemmer()
word_data = "It originated from the idea that there are readers who prefer learning new skills from the comforts of their drawing rooms"
# First Word tokenization
nltk_tokens = nltk.word_tokenize(word_data)
#Next find the roots of the word
for w in nltk_tokens:
print "Actual: %s Stem: %s" % (w,porter_stemmer.stem(w))
当我们执行上面的代码时,它会产生以下结果。
Actual: It Stem: It
Actual: originated Stem: origin
Actual: from Stem: from
Actual: the Stem: the
Actual: idea Stem: idea
Actual: that Stem: that
Actual: there Stem: there
Actual: are Stem: are
Actual: readers Stem: reader
Actual: who Stem: who
Actual: prefer Stem: prefer
Actual: learning Stem: learn
Actual: new Stem: new
Actual: skills Stem: skill
Actual: from Stem: from
Actual: the Stem: the
Actual: comforts Stem: comfort
Actual: of Stem: of
Actual: their Stem: their
Actual: drawing Stem: draw
Actual: rooms Stem: room
词形还原类似于词干,但它为词语带来了语境。因此,通过将具有相似含义的词语与一个词语联系起来,它更进了一步。 例如,如果一个段落有像汽车,火车和汽车这样的词,那么它将把它们全部链接到汽车上。 在下面的程序中,我们使用WordNet词汇数据库进行词形还原。
import nltk
from nltk.stem import WordNetLemmatizer
wordnet_lemmatizer = WordNetLemmatizer()
word_data = "It originated from the idea that there are readers who prefer learning new skills from the comforts of their drawing rooms"
nltk_tokens = nltk.word_tokenize(word_data)
for w in nltk_tokens:
print "Actual: %s Lemma: %s" % (w,wordnet_lemmatizer.lemmatize(w))
当我们执行上面的代码时,它会产生以下结果。
Actual: It Lemma: It
Actual: originated Lemma: originated
Actual: from Lemma: from
Actual: the Lemma: the
Actual: idea Lemma: idea
Actual: that Lemma: that
Actual: there Lemma: there
Actual: are Lemma: are
Actual: readers Lemma: reader
Actual: who Lemma: who
Actual: prefer Lemma: prefer
Actual: learning Lemma: learning
Actual: new Lemma: new
Actual: skills Lemma: skill
Actual: from Lemma: from
Actual: the Lemma: the
Actual: comforts Lemma: comfort
Actual: of Lemma: of
Actual: their Lemma: their
Actual: drawing Lemma: drawing
Actual: rooms Lemma: room