计算词和词组频率的Python nltk

Question

我正在使用NLTK并尝试将单词短语计数到特定文档的某个长度以及每个短语的频率.我将字符串标记为获取数据列表.

from nltk.util import ngrams
from nltk.tokenize import sent_tokenize, word_tokenize
from nltk.collocations import *


data = ["this", "is", "not", "a", "test", "this", "is", "real", "not", "a", "test", "this", "is", "this", "is", "real", "not", "a", "test"]

bigrams = ngrams(data, 2)

bigrams_c = {}
for b in bigrams:
    if b not in bigrams_c:
        bigrams_c[b] = 1
    else:
        bigrams_c[b] += 1

上面的代码给出和输出如下:

(('is', 'this'), 1)
(('test', 'this'), 2)
(('a', 'test'), 3)
(('this', 'is'), 4)
(('is', 'not'), 1)
(('real', 'not'), 2)
(('is', 'real'), 2)
(('not', 'a'), 3)

这是我正在寻找的部分内容.

我的问题是,是否有更方便的方法来说明长度为4或5的短语而不重复此代码只更改计数变量？

Answer 1

因为你标记了这个nltk,所以这里是如何使用nltk的方法,它具有比标准python集合更多的功能.

from nltk import ngrams, FreqDist
all_counts = dict()
for size in 2, 3, 4, 5:
    all_counts[size] = FreqDist(ngrams(data, size))

字典的每个元素all_counts都是ngram频率的字典.例如,您可以获得五个最常见的三元组:

all_counts[3].most_common(5)