Dear Pallavi Jog

Please go through this link. It may improve your knowledge.

Regards

https://www.kdnuggets.com/2019/04/text-preprocessing-nlp-machine-learning.html

Hi,

There are multiple options, one is to first detect the misspelled word

see this: https://towardsdatascience.com/essential-text-correction-process-for-nlp-tasks-f731a025fcc3

, correct it, and then to the classical preprocessing e.g. via nltk.

That the word will be only corrected even without taking the context into consideration might be in most applications not a problem. But as always it depends.

Dear Pallavi Jog

Please go through this link. It may improve your knowledge.

Regards

https://www.kdnuggets.com/2019/04/text-preprocessing-nlp-machine-learning.html

Thanks a lot Mustafa Sabah Taha and Björn Preuss .. will check out these links..

Have you consider building a spell checker function, you can use pattern en library to do this. This will first require you to write a lengthening function that will help you rip off repeated characters in words. Lengthening function should remove any third letter that is repeated in a single word. e.g "burrrst" will return "burrst" since English words does not have more than two repeated letters per word.

After the lengthening function, you can use the pattern library in python to correct wrongly spelt words.