NLP计算词相关关系之word2vec

import gensiminp='D:\python_noweightpathway\TIA\TIAxmmc.txt'outp1 = 'D:\python_noweightpathway\TIA\model'outp2 = 'D:\python_noweightpathway\TIA\vector'sentences=[]#读取数据生成sentencesfile=open(u'D:\python_noweightpathway\TIA\TIAxmmc.txt',encoding='utf-8')sentences = gensim.models.word2vec.LineSentence(file)model = gensim.models.Word2Vec(sentences, size=100, window=6, min_count=5, workers=8)model.save(outp1)

读取模型

# -*- coding: utf-8 -*-# <nbformat>3.0</nbformat>import gensim# 导入模型model = gensim.models.Word2Vec.load("D:\python_noweightpathway\TIA\model")print(model.wv.most_similar(positive=['瑞舒伐他汀钙片']))