Project 1 补交

related.py

+
+import numpy as np
+import heapq
+
+glovefile = open("glove.6B.200d.txt","r",encoding="utf-8")  
+ #key:单词 val:矢量
+emb = {}
+for line in glovefile:
+    word, vec = line.split(maxsplit=1)
+    vec = np.fromstring(vec, 'float', sep = ' ')
+    emb[word] = vec
+
+related = []
+for word in emb:
+    related.append(word)
+
+
+# 计算词与词之间的相似度
+
+def cos_sim(x,y):
+    return x.dot(y)/(np.linalg.norm(x)*np.linalg.norm(y))
+
+
+
+for i in range(len(related)):
+    sim_h = []
+    for word2 in emb:
+
+        if word2 != related[i]:
+            vec1, vec2 = emb[related[i]], emb[word2]
+            sim = cos_sim(vec1,vec2)
+            heapq.heappush(sim_h,(sim,word2))
+    
+    related_words = heapq.nsmallest(10, sim_h)
+    for word in related_words:
+        related[i] = related[i] + ' ' + word[1]
+
+    if ((i/len(related))*100)//10 == 0:
+        print("Finish %d %" % i/len(related))*100) 
+
+
+with open('related.txt', 'w') as f:
+    f.writelines("%s\n" % i for i in related)
+
+