import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
from gensim.test.utils import datapath, get_tmpfile
from gensim.models import KeyedVectors
from gensim.scripts.glove2word2vec import glove2word2vec

# glove:相关的词，词向量的大小，比word2vec强

# 读取 Excel 文件
df = pd.read_excel('../datas/hebing.xlsx', sheet_name='Sheet1')

# glove2word2vec(df)
# model = KeyedVectors.load_word2vec_format(df)
# most_similar = model.most_similar('修复')
# print(most_similar)
