我有一个将单词转换为矢量的代码。下面是我的代码:
# word_to_vec_demo.py
from gensim.models import word2vec
import logging
logging.basicConfig(format='%(asctime)s : \
%(levelname)s : %(message)s', level=logging.INFO)
sentences = [['In', 'the', 'beginning', 'Abba','Yahweh', 'created', 'the',
'heaven', 'and', 'the', 'earth.', 'And', 'the', 'earth', 'was',
'without', 'form,', 'and', 'void;', 'and', 'darkness', 'was',
'upon', 'the', 'face', 'of', 'the', 'deep.', 'And', 'the',
'Spirit', 'of', 'Yahweh', 'moved', 'upon', 'the', 'face', 'of',
'the', 'waters.']]
model = word2vec.Word2Vec(sentences, size=10, min_count=1)
print("Vector for \'earth\' is: \n")
print(model.wv['earth'])
print("\nEnd demo")
输出是
Vector for 'earth' is:
[-0.00402722 0.0034133 0.01583795 0.01997946 0.04112177 0.00291858
-0.03854967 0.01581967 -0.02399057 0.00539708]
是否可以从向量数组编码到单词?如果是,我将如何在Python中实现它?
最佳答案
您可以使用模型中的similar_by_vector()方法按向量查找前N个最相似的词。
希望这可以帮助。