通过gensim做两句话的语义相似度分析,请提供代码
时间: 2023-06-08 14:05:17 浏览: 50
好的,下面是使用gensim计算两句话的语义相似度的Python代码:
```
from gensim.models import Word2Vec
from gensim.similarities import WmdSimilarity
# 构建词向量模型
sentences = [["this", "is", "a", "test"], ["this", "is", "another", "test"]]
model = Word2Vec(sentences, min_count=1)
# 计算两句话的语义相似度
sentence1 = "this is a test sentence"
sentence2 = "this is another test sentence"
documents = [sentence1.split(), sentence2.split()]
instance = WmdSimilarity(documents, model)
similarity = instance[0][1]
print("两句话的语义相似度为:", similarity)
```
这段代码中,我们首先使用gensim构建了一个词向量模型,然后计算了两句话"this is a test sentence"和"this is another test sentence"的语义相似度。具体计算方法是使用WmdSimilarity类,它可以计算文档间的Word Mover's Distance(WMD)相似度,即两篇文档之间单词平移的最小距离。最后输出两句话的语义相似度即可。