如何將句子加載到Python gensim中？

Question

我試圖在Python中使用gensim自然語言處理庫中的word2vec模塊。

文檔說要初始化模型：

from gensim.models import word2vec
model = Word2Vec(sentences, size=100, window=5, min_count=5, workers=4)

gensim對輸入句子的期望是什么格式？ 我有原始文本

"the quick brown fox jumps over the lazy dogs"
"Then a cop quizzed Mick Jagger's ex-wives briefly."
etc.

我需要在word2fec發布哪些額外的處理？

---

更新：這是我嘗試過的。 當它加載句子時，我什么也得不到。

>>> sentences = ['the quick brown fox jumps over the lazy dogs',
             "Then a cop quizzed Mick Jagger's ex-wives briefly."]
>>> x = word2vec.Word2Vec()
>>> x.build_vocab([s.encode('utf-8').split( ) for s in sentences])
>>> x.vocab
{}

Answer 1

utf-8句子列表 。 您還可以從磁盤流式傳輸數據。

確保它是utf-8 ，並將其拆分：

sentences = [ "the quick brown fox jumps over the lazy dogs",
"Then a cop quizzed Mick Jagger's ex-wives briefly." ]
word2vec.Word2Vec([s.encode('utf-8').split() for s in sentences], size=100, window=5, min_count=5, workers=4)

Answer 2

就像alKid指出的那樣，把它變成utf-8 。

談論另外兩件可能需要擔心的事情。

1. 輸入太大，您正在從文件中加載它。
2. 從句子中刪除停用詞。

您可以執行以下操作，而不是將大型列表加載到內存中：

import nltk, gensim
class FileToSent(object):    
    def __init__(self, filename):
        self.filename = filename
        self.stop = set(nltk.corpus.stopwords.words('english'))

    def __iter__(self):
        for line in open(self.filename, 'r'):
        ll = [i for i in unicode(line, 'utf-8').lower().split() if i not in self.stop]
        yield ll

接着，

sentences = FileToSent('sentence_file.txt')
model = gensim.models.Word2Vec(sentences=sentences, window=5, min_count=5, workers=4, hs=1)