搬运工看起来不像

Question

我对python还不太熟悉，并用书中的示例进行练习。
有谁能解释一下为什么当我试图用这段代码来做一些例子时，什么都没有改变？

>>> from nltk.stem import PorterStemmer
>>> stemmer=PorterStemmer()
>>> stemmer.stem('numpang wifi stop gadget shopping')
'numpang wifi stop gadget shopping'

但当我这么做的时候

>>> stemmer.stem('shopping')
'shop'

Answer 1

词干是把一个给定的单词还原成它的词根或屈折形式的过程，这里你要试着把整个句子都词干化

遵循以下步骤：

from nltk.tokenize import word_tokenize
from nltk.stem import PorterStemmer
sentence = "numpang wifi stop gadget shopping"
tokens = word_tokenize(sentence)
stemmer=PorterStemmer()

Output=[stemmer.stem(word) for word in tokens]

Answer 2

试试这个：

from nltk.stem import PorterStemmer
from nltk.tokenize import word_tokenize

stemmer = PorterStemmer()

some_text = "numpang wifi stop gadget shopping"

words = word_tokenize(some_text)

for word in words:
    print(stemmer.stem(word))

Answer 3

试试这个：

res = ",".join([ stemmer.stem(kw) for kw in 'numpang wifi stop gadget shopping'.split(" ")])

问题是，可能，词干分析器只对单个单词起作用。你的字符串没有“根”字，而单个“购物”字有“商店”的根。所以你得分别计算词干

编辑：

从他们的源代码->

Stemming algorithms attempt to automatically remove suffixes (and in some
cases prefixes) in order to find the "root word" or stem of a given word. This
is useful in various natural language processing scenarios, such as search.

所以我想你真的是被迫自己拆线