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 ## Description
 
-Edit distance is a way of quantifying how dissimilar two strings are to one another by counting the minimum number of operations required to transform one string into the other. The distance between the two documents is defined as "The minimum number of insertions, deletions, and substitutions required to transform one string into the other". Edit-based distances for which such weights can be defined are usually refered to as generalized distances. These methods are independent of a searching algorithm, i.e. Levenshtein or Hamming edit distances can be applied separately to a searching algorithm.
+Edit distance is a way of quantifying how dissimilar or similar two strings are to one another by counting the minimum number of operations required to transform one string into the other. The distance between the two documents is defined as "The minimum number of insertions, deletions, and substitutions required to transform one string into the other". Edit-based distances for which such weights can be defined are usually refered to as generalized distances. These methods are independent of a searching algorithm, i.e. Levenshtein or Hamming edit distances can be applied separately to a searching algorithm.
 
 Edit distances find applications in natural language processing, where automatic spelling correction can determine candidate corrections for a misspelled word by selecting words from a dictionary that have a low distance to the word in question.