95、自然语言处理svd词向量

import numpy as np
import matplotlib.pyplot as plt
la = np.linalg
words = ["I","like","enjoy","deep","learning","NLP","flying","."]
X = np.array([[0,2,1,0,0,0,0,0],
              [2,0,0,1,0,1,0,0],
              [1,0,0,0,0,0,1,0],
              [0,1,0,0,1,0,0,0],
              [0,0,0,1,0,0,0,1],
              [0,1,0,0,0,0,0,1],
              [0,0,1,0,0,0,0,1],
              [0,0,0,0,1,1,1,0]])
U,s,Vh=la.svd(X, full_matrices=False)
for i in range(len(words)):
    print(U[i,1],U[i,1],words[i])
    plt.text(U[i,0],U[i,1],words[i])
plt.xlim(-1,1)
plt.ylim(-1,1)
plt.show()