| Access | Constructor and Description |
|---|---|
| public |
| Modifier and Type | Method and Description |
|---|---|
| public final double | distance(final String s1, final String s2)
Implements info. Equivalent to distance(s1, s2, Integer.MAX_VALUE). |
| public final double | Returns: The computed Levenshtein distance.The first string to compare. s1, final String The second string to compare. s2, final int The maximum result to compute before stopping. This
means that the calculation can terminate early if you
only care about strings with a certain similarity.
Set this to Integer.MAX_VALUE if you want to run the
calculation to completion in every case. limit)The Levenshtein distance, or edit distance, between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. |
| Levenshtein | back to summary |
|---|---|
| public Levenshtein() | |
| distance | back to summary |
|---|---|
| public final double distance(final String s1, final String s2) Implements info. Equivalent to distance(s1, s2, Integer.MAX_VALUE). | |
| distance | back to summary |
|---|---|
| public final double distance(final String s1, final String s2, final int limit) The Levenshtein distance, or edit distance, between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. http://en.wikipedia.org/wiki/Levenshtein_distance It is always at least the difference of the sizes of the two strings. It is at most the length of the longer string. It is zero if and only if the strings are equal. If the strings are the same size, the Hamming distance is an upper bound on the Levenshtein distance. The Levenshtein distance verifies the triangle inequality (the distance between two strings is no greater than the sum Levenshtein distances from a third string). Implementation uses dynamic programming (Wagner–Fischer algorithm), with only 2 rows of data. The space requirement is thus O(m) and the algorithm runs in O(mn).
| |