问题描述
我正在尝试使用WMD查找相似的句子。
DATE TEXT
2019-01-12 The sky is blue and beautiful.
2019-01-12 love this blue and beautiful sky!
2019-01-12 The quick brown fox jumps over the lazy dog.
2019-01-12 A king’s breakfast has sausages,ham,bacon,eggs,toast and beans
2019-01-12 I love green eggs,sausages and bacon!
2020-01-13 The brown fox is quick and the blue dog is lazy!
2020-01-13 The sky is very blue and the sky is very beautiful today
2019-01-21 The dog is lazy but the brown fox is quick!
2020-01-12 President greets the press in Chicago
2020-01-12 Obama speaks in Illinois
为了找到这两个句子中的任何一个之间的相似性（我应该将其应用于所有句子），我尝试如下使用WMD（针对两个字符串）：
import numpy as np
import pandas as pd
# calculate distance between 2 responses using wmd
def find_similar_sentences(sentence_1,sentence_2):
distance = model.wv.wmdistance(sentence_1,sentence_2)
return distance
# create distance matrix
tokenized_sentences = [s.split() for s in df[col]]
l = len(tokenized_sentences)
distances = np.zeros((l,l))
for i in range(l):
for j in range(l):
distances[i,j] = find_similar_sentences(tokenized_sentences[i],tokenized_sentences[j])
# make pandas dataframe
labels = ['sentence' + str(i + 1) for i in range(l)]
df = pd.DataFrame(data=distances,index=labels,columns=labels)
print(df)
我期望这样的事情：
DATE TEXT Similar Sentence
2019-01-12 The sky is blue and beautiful. [love this blue and beautiful sky!,The sky is very blue and the sky is very beautiful today]
2019-01-12 love this blue and beautiful sky! [The sky is blue and beautiful.,The sky is very blue and the sky is very beautiful today]
2019-01-12 The quick brown fox jumps over the lazy dog. [The brown fox is quick and the blue dog is lazy!,The dog is lazy but the brown fox is quick!]
2019-01-12 A king’s breakfast has sausages,toast and beans [I love green eggs,sausages and bacon!]
2019-01-12 I love green eggs,sausages and bacon! [A king’s breakfast has sausages,toast and beans ]
2020-01-13 The brown fox is quick and the blue dog is lazy! [The quick brown fox jumps over the lazy dog.,The dog is lazy but the brown fox is quick!]
2020-01-13 The sky is very blue and the sky is very beautiful today [The sky is blue and beautiful.,love this blue and beautiful sky! ]
2019-01-21 The dog is lazy but the brown fox is quick! [he quick brown fox jumps over the lazy dog.,The brown fox is quick and the blue dog is lazy! ]
2020-01-12 President greets the press in Chicago [Obama speaks in Illinois]
2020-01-12 Obama speaks in Illinois [President greets the press in Chicago]
其中Similar_Sentence列是根据高于所选阈值的句子填充的。
能否请您告诉我如何通过行而不是字符串扩展上面的代码，以便获得与预期输出中显示的列相似的内容（与阈值无关）？
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
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