小编dze*_*lee的帖子

gensimwv.most_similar返回语音上接近的单词（相似的声音），而不是语义上相似的单词。这是正常的吗？为什么会发生这种情况？

以下是有关的文档most_similar：https://radimrehurek.com/gensim/models/keyedvectors.html#gensim.models.keyedvectors.WordEmbeddingsKeyedVectors.most_similar

In [144]: len(vectors.vocab)
Out[144]: 32966

... 

In [140]: vectors.most_similar('fight')
Out[140]:
[('Night', 0.9940935373306274),
 ('knight', 0.9928507804870605),
 ('fright', 0.9925899505615234),
 ('light', 0.9919329285621643),
 ('bright', 0.9914385080337524),
 ('plight', 0.9912853240966797),
 ('Eight', 0.9912533760070801),
 ('sight', 0.9908033013343811),
 ('playwright', 0.9905624985694885),
 ('slight', 0.990411102771759)]

In [141]: vectors.most_similar('care')
Out[141]:
[('spare', 0.9710584878921509),
 ('scare', 0.9626247882843018),
 ('share', 0.9594929218292236),
 ('prepare', 0.9584596157073975),
 ('aware', 0.9551078081130981),
 ('negare', 0.9550014138221741),
 ('glassware', 0.9507938027381897),
 ('Welfare', 0.9489598274230957),
 ('warfare', 0.9487678408622742),
 ('square', 0.9473209381103516)]

训练数据包含学术论文，这是我的训练脚本：

from gensim.models.fasttext import FastText as FT_gensim
import gensim.models.keyedvectors as word2vec

dim_size = 300
epochs = 10
model = …