Is any data that is related to the frequency of the types of people's mistakes, when they spell a word Are you I am not referring myself to words, but Tiger errors that are made by Typist. For example, I personally make the transfer error after most entry errors (which do not include a letter I want), replacement errors and finally, entry errors. However, it would not surprise me to find out that typing a wrong letter (a replacement error, such as a cat instead of a cat) is more often than not involving the letter.
My aim is to be able to correct one word when I have only the input of the original user, it is being considered that if one type of mistake is more than the others , It is more likely that correcting the word is correct through such type of operation. I usually do not object to using the misplaced database of databases, but I prefer an algorithm solution based on a corpus - especially if it is fast.
You can calculate something between the typed words and the words given in a dictionary You can try to use I'm not sure that's what you want.
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