Python，比较计数器中的字符串并分配给最接近的匹配项

Question

I have a list of input text written by humans. This text is imported to python and a Counter is generated. In the Counter, all the inputs from humans are listed and counted. At the end obtain something like:

"Input 1" : 3,

"Input 2" : 1, ...

The problem i have is that sometimes these inputs have spelling mistakes or are missing a space between words etc. How could I go through this list and compare it to some reference Inputs and asign to each counter row the total counts of the well written Inputs + the ones coming from the most similar Inputs with spelling mistakes. I know this falls on the NLP field but i can't really find a way to do this in a counter

Answer 1

在不应用任何 ML 的情况下，我的第一次尝试是使用Levenshtein Distance这将让您在字符串之间生成一些具体的相似性，并对“无错误”字符串和有错字的字符串之间的联系做出有根据的猜测。