gensim加载word2vec训练结果(bin文件)并进行相似度实验

# -*- coding: utf-8 -*-  
import gensim  

# 导入模型
model = gensim.models.KeyedVectors.load_word2vec_format('vectors.bin', binary=True)

# 得到两组词的相似度
list1 = [u'核能']
list2 = [u'电能']
list3 = [u'电力']
list_sim1 =  model.n_similarity(list1, list2)
print list_sim1
list_sim2 = model.n_similarity(list2, list3)
print list_sim2, '\n'

# 得到一组词中最无关的词
list4 = [u'汽车', u'火车', u'飞机', u'北京']
print model.doesnt_match(list4)
print '\n'

# 得到与一个词最相关的若干词及相似程度
result = model.most_similar(u'脱水工艺')
for each in result:
    print each[0] , each[1]