Calculate Levenshtein Disance

String 1

String 2


What is the Levenshtein Distance?

Levenshtein Distance, named after the Soviet mathematician Vladimir Levenshtein, is a metric used to quantify the dissimilarity between two strings. It calculates the minimum number of single-character edits needed to transform one string into another, where edits can be insertions, deletions, or substitutions. This distance measure finds widespread applications in various domains, including computer science, bioinformatics, and natural language processing.

In computer science, it's employed for tasks such as spell-checking, approximate string matching, and plagiarism detection. In bioinformatics, Levenshtein Distance helps analyze genetic sequences by determining the similarity between DNA or protein sequences. Furthermore, it's utilized in information retrieval systems to identify relevant documents based on textual similarities.

The algorithm for calculating Levenshtein Distance typically involves dynamic programming techniques to efficiently find the minimum edit distance. Despite its computational complexity, Levenshtein Distance remains a fundamental tool for measuring the similarity between strings and plays a vital role in many algorithmic and data processing tasks.

How to calculate a Levenshtein Distance?

The short version is that the Levenshtein Distance is the number of changes that need be to be made to one string to change it to another string. It considers 3 types of changes.

  • Insertion of a character
  • Deletion of a character
  • Replacement of a character

For example, the Levenshtein Distance between beer and beard is 2. No change because of the first two characters, they're the same. The third character is different, so that's a replacement and the first point in the distance. Fourth character is r in both strings, so no change. The last character in the second string is an addition, and point number two.

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