有效地遍历一串字符串以获得成对的WMD距离矩阵

Question

我正在尝试从列表字符串（报纸文章）生成成对距离的矩阵。

WMD距离未在scipy.spatial.distance.pdist中实现，因此我将此实现：https://github.com/src-d/wmd-relax链接到SpaCy。但是，我不知道如何遍历列表以生成距离矩阵。

Answer 1

根据文档：

import spacy
import wmd
import numpy as np


nlp = spacy.load('en_core_web_md')
nlp.add_pipe(wmd.WMD.SpacySimilarityHook(nlp), last=True)

# given articles is a list of strings
docs = [nlp(article) for article in articles]

# matrix is just a list of lists in terms of Python objects
m = []
for doc1 in docs:
    row = []
    for doc2 in docs:
        # if distance is similarity function
        row.append(doc1.similarity(doc2))
    m.append(row)

result = np.matrix(m)

Numpy matrix doc