Levenshtein Distance Calculator

This online calculator measures the Levenshtein distance between two strings.

The Levenshtein distance (or edit distance) between two strings is the number of deletions, insertions, or substitutions required to transform the source string into the target string. For example, if the source string is “book” and the target string is “back”, to transform “book” into “back” you need to replace the first “o” with “a” and the second “o” with “c”, without any additional deletions or insertions. Thus, the Levenshtein distance between “book” and “back” is 2.

More information about the Levenshtein distance algorithm and its applications can be found below the calculator.

Старі URL (один на рядок)Нові URL (один на рядок)Мінімальна схожість: 70%ПорівнятиОчиститиЕкспорт CSVПідказка: для великих списків (>1000) використовуйте серверний розрахунок. Дані не зберігаються на сервері після відповіді.

Levenshtein Distance Algorithms and Their Applications

The Levenshtein distance between two strings a and b (of lengths |a| and |b| respectively) is defined as lev(a,b), where
{\displaystyle \qquad \operatorname {lev} (a,b)={\begin{cases}|a|&{\text{ if }}|b|=0,\\|b|&{\text{ if }}|a|=0,\\\ operatorname {lev} (\operatorname {tail} (a),\operatorname {tail} (b))&{\text{ if }}a[0]=b[0]\\1+\min {\begin{cases}\operatorname {lev} (\operatorname {tail} (a),b)\\\operatorname {lev} (a,\operatorname {tail} (b))\\\operatorname {lev} (\operatorname {tail} (a),\operatorname {tail} (b))\\\end{cases}}&{\text{ otherwise.}}\end{cases}}}.

The Levenshtein distance is named after the scientist Vladimir Levenshtein, who developed this metric in 1965.

There are several algorithms for computing the Levenshtein distance:

• Recursive — a simple algorithm that directly follows the definition
• Iterative with a full matrix — the one used in the calculator above
• Iterative with two rows of the matrix

More detailed information and pseudocode implementations for all algorithms can be found in the article “Levenshtein Distance” on Wikipedia.

It has been proven that the Levenshtein distance cannot be computed in time significantly better than quadratic, which makes its use impractical for comparing long strings, as the computational cost is proportional to the product of the string lengths. However, edit distance can be effectively used to search for occurrences of a short string, for example taken from a dictionary, within a long string. This is useful for spell checkers, optical character recognition (OCR) correction systems, and similar products.

You can also use our online Levenshtein distance tool for matching URL addresses, which helps SEO and marketing specialists quickly generate a list of URLs for creating 301 redirect tables from old URLs to new ones.

Simply enter old addresses into the “Old URLs (one per line)” field and new ones into the “New URLs (one per line)” field, then set the minimum similarity slider and compare to get the results.

After checking all URLs, you can export the data to a CSV table with a single click.

Important to know about the “Online Levenshtein Distance Calculator” by SEOGeeks:

• Checking up to 1,000 URLs is performed instantly using JavaScript.
• Checking a larger number of URLs is performed using server-side computation, but the data is NOT stored on the server.