如何使用gensim从语料库中提取短语

Question

为了预处理语料库,我计划从语料库中提取常用短语,为此我尝试在gensim中使用短语模型,我尝试下面的代码,但它没有给我想要的输出.

我的代码

from gensim.models import Phrases
documents = ["the mayor of new york was there", "machine learning can be useful sometimes"]

sentence_stream = [doc.split(" ") for doc in documents]
bigram = Phrases(sentence_stream)
sent = [u'the', u'mayor', u'of', u'new', u'york', u'was', u'there']
print(bigram[sent])

产量

[u'the', u'mayor', u'of', u'new', u'york', u'was', u'there']

但它应该成为

[u'the', u'mayor', u'of', u'new_york', u'was', u'there']

但是当我试图打印火车数据的词汇时,我可以看到二元组,但它不能使用测试数据,我哪里出错了？

print bigram.vocab

defaultdict(<type 'int'>, {'useful': 1, 'was_there': 1, 'learning_can': 1, 'learning': 1, 'of_new': 1, 'can_be': 1, 'mayor': 1, 'there': 1, 'machine': 1, 'new': 1, 'was': 1, 'useful_sometimes': 1, 'be': 1, 'mayor_of': 1, 'york_was': 1, 'york': 1, 'machine_learning': 1, 'the_mayor': 1, 'new_york': 1, 'of': 1, 'sometimes': 1, 'can': 1, 'be_useful': 1, 'the': 1}) 

Answer 1

我得到了问题的解决方案,有两个参数我没有处理它应该传递给Phrases()模型,那些是

1. min_count忽略总收集数低于此数的所有单词和双字母组.默认值为5

2. 阈值表示形成短语的阈值(更高表示更少的短语).如果(cnt(a,b) - min_count)*N /(cnt(a)*cnt(b))>阈值,则接受单词a和b的短语,其中N是总词汇量大小.默认值为10.0

我的上述列车数据有两个语句,阈值为0,所以我改变了训练数据集并添加了这两个参数.

我的新代码

from gensim.models import Phrases
documents = ["the mayor of new york was there", "machine learning can be useful sometimes","new york mayor was present"]

sentence_stream = [doc.split(" ") for doc in documents]
bigram = Phrases(sentence_stream, min_count=1, threshold=2)
sent = [u'the', u'mayor', u'of', u'new', u'york', u'was', u'there']
print(bigram[sent])

产量

[u'the', u'mayor', u'of', u'new_york', u'was', u'there']

Gensim非常棒:)