Question

我正在尝试构建一个拼写校正器使用图。

步骤1：我使用一些书籍作为语料库和Python networkx包来构建直接图形节点是单词，并且我在此图形中为每个节点添加一个名为“DISTANCE”的属性，表示两个单词之间的距离。

 example:
 graph[‘love’][‘you’][‘DISTANCE’] = 37,means, in my corpus，‘love you’ appeals 37 times.
 graph[‘you’][‘love’][‘DISTANCE’] = 39,means, in my corpus，‘you love’ appeals 39 times.

显然，图形['爱'] ['你']和图形['你'] ['爱']是不同的。我的问题是当我完成一些操作时，我得到一个列表包含列表。像这样，（长度是可变的）：

[

[who,whom,whose],
[are,all,],
[that,than,this]

]

每个子列表包含可能正确的单词，我的问题是我想将此列表转换为此。

 [
 [who,are,that],
 [who,are,than],
 [who,are,this],
 [who,all,that],
 [who,all,than],
 [who,all,this],
 [whom,are,that],
 [whom,are,than],
 [whom,are,this],
 [whom,all,that],
 [whom,all,than],
 [whom,all,this],
 [whose,are,that],
 [whose,are,than],
 [whose,are,this],
 [whose,all,that],    
 [whose,all,than],
 [whose,all,this],
 ]

所以我可以计算出距离，确定最佳距离。

我是算法中的新手，你知道哪种算法能满足这个要求吗？如果你有一些建议可以帮助我使这个拼写纠正器更有效，请告诉我。

谢谢！

Answer 1

您可以使用itertools.product进行转换：

from itertools import product

d = [
    ['who','whom','whose'],
    ['are','all'],
    ['that','than','this']
]

print list(product(*d))

格式化输出：

[
    ('who', 'are', 'that'), 
    ('who', 'are', 'than'), 
    ('who', 'are', 'this'), 
    ('who', 'all', 'that'), 
    ('who', 'all', 'than'), 
    ('who', 'all', 'this'), 
    ('whom', 'are', 'that'), 
    ('whom', 'are', 'than'), 
    ('whom', 'are', 'this'), 
    ('whom', 'all', 'that'), 
    ('whom', 'all', 'than'), 
    ('whom', 'all', 'this'), 
    ('whose', 'are', 'that'),
    ('whose', 'are', 'than'), 
    ('whose', 'are', 'this'), 
    ('whose', 'all', 'that'), 
    ('whose', 'all', 'than'), 
    ('whose', 'all', 'this')
]

在python中将列表转换为矩阵

1 个答案: