如何使用NLTK Collocations获得三元组的PMI分数?蟒蛇

时间:2014-01-15 03:38:21

标签: python nlp nltk collocation

我知道如何使用NLTK获得bigram和trigram搭配,并将它们应用到我自己的语料库中。代码如下。

我唯一的问题是如何用PMI值打印出birgram?我多次搜索NLTK文档。这要么是我缺少某些东西,要么就是不存在。

import nltk
from nltk.collocations import *

myFile = open("large.txt", 'r').read()
myList = myFile.split()
myCorpus = nltk.Text(myList)
trigram_measures = nltk.collocations.TrigramAssocMeasures()
finder = TrigramCollocationFinder.from_words((myCorpus))

finder.apply_freq_filter(3)
print finder.nbest(trigram_measures.pmi, 500000)

2 个答案:

答案 0 :(得分:4)

如果您查看nlkt.collocations.TrigramCollocationFinder的源代码(请参阅http://www.nltk.org/_modules/nltk/collocations.html),您会发现它返回TrigramCollocationFinder().score_ngrams

def nbest(self, score_fn, n):
    """Returns the top n ngrams when scored by the given function."""
    return [p for p,s in self.score_ngrams(score_fn)[:n]]

因此,您可以直接调用score_ngrams()而无需获取nbest,因为它无论如何都会返回已排序的列表。

def score_ngrams(self, score_fn):
    """Returns a sequence of (ngram, score) pairs ordered from highest to
    lowest score, as determined by the scoring function provided.
    """
    return sorted(self._score_ngrams(score_fn),
                  key=_itemgetter(1), reverse=True)

尝试:

import nltk
from nltk.collocations import *
from nltk.tokenize import word_tokenize

text = "this is a foo bar bar black sheep  foo bar bar black sheep foo bar bar black sheep shep bar bar black sentence"

trigram_measures = nltk.collocations.TrigramAssocMeasures()
finder = TrigramCollocationFinder.from_words(word_tokenize(text))

for i in finder.score_ngrams(trigram_measures.pmi):
    print i

<强> [OUT]:

(('this', 'is', 'a'), 9.047123912114026)
(('is', 'a', 'foo'), 7.46216141139287)
(('black', 'sheep', 'shep'), 5.46216141139287)
(('black', 'sheep', 'foo'), 4.877198910671714)
(('a', 'foo', 'bar'), 4.462161411392869)
(('sheep', 'shep', 'bar'), 4.462161411392869)
(('bar', 'black', 'sheep'), 4.047123912114026)
(('bar', 'black', 'sentence'), 4.047123912114026)
(('sheep', 'foo', 'bar'), 3.877198910671714)
(('bar', 'bar', 'black'), 3.047123912114026)
(('foo', 'bar', 'bar'), 3.047123912114026)
(('shep', 'bar', 'bar'), 3.047123912114026)

答案 1 :(得分:1)

我认为你正在寻找score_ngram。无论如何,您不需要打印功能。只是自己输出...

trigrams = finder.nbest(trigram_measures.pmi, 500000)
print [(x, finder.score_ngram(trigram_measures.pmi, x[0], x[1], x[2])) for x in trigrams]