from gensim.models import word2vec
model = word2vec.Word2Vec.load('wiki.model')
print(model.wv.most_similar(positive=['Python','파이썬'])[0:5])
print(model.wv.most_similar(positive=['아빠','여성'],negative=['남성'])[0:5])
print(model.wv.most_similar(positive=['아빠'],negative=['남성']))
print(model.wv.most_similar(positive=['왕자','여성'],negative=['남성'])[0:5])
print(model.wv.most_similar(positive=['서울','일본'],negative=['한국'])[0:5])
print(model.wv.most_similar(positive=['서울','중국'],negative=['한국'])[0:5])
print(model.wv.most_similar(positive=['서울','맛집'])[0:5])
print(model.wv.most_similar(positive=['오른쪽','남자'],negative=['왼쪽'])[0:5])