# coding: utf-8
import sys
sys.path.append('..')
from common.util import most_similar, analogy
import pickle
pkl_file = '../../chap4/cbow_params.pkl'
# pkl_file = 'skipgram_params.pkl'
with open(pkl_file, 'rb') as f:
params = pickle.load(f)
word_vecs = params['word_vecs']
word_to_id = params['word_to_id']
id_to_word = params['id_to_word']
# 가장 비슷한(most similar) 단어 뽑기
querys = ['you', 'year', 'car', 'toyota']
for query in querys:
most_similar(query, word_to_id, id_to_word, word_vecs, top=5)
# 유추(analogy) 작업
print('-' * 50)
analogy('king', 'man', 'queen', word_to_id, id_to_word, word_vecs)
analogy('take', 'took', 'go', word_to_id, id_to_word, word_vecs)
analogy('car', 'cars', 'child', word_to_id, id_to_word, word_vecs)
analogy('good', 'better', 'bad', word_to_id, id_to_word, word_vecs)
import sys
sys.path.append('..')
from common.util import preprocess, create_co_matrix, most_similar
text = 'You say goodbye and I say hello'
corpus, word_to_id, id_to_word = preprocess(text)
vocab_size = len(word_to_id)
C = create_co_matrix(corpus, vocab_size)
most_similar('you', word_to_id, id_to_word, C, top=5)
import sys
sys.path.append("..")
from common.util import preprocess, create_co_matrix, most_similar
text = "You say goodbye and I say hello."
corpus, word_to_id, id_to_word = preprocess(text)
vocab_size = len(word_to_id)
C = create_co_matrix(corpus, vocab_size)
most_similar("you", word_to_id, id_to_word, C, top=5)