info.debatty.java.stringsimilarity

Class NormalizedLevenshtein

java.lang.Object

info.debatty.java.stringsimilarity.NormalizedLevenshtein

All Implemented Interfaces:

NormalizedStringDistance, NormalizedStringSimilarity, StringDistance, StringSimilarity, Serializable

@Immutable
public class NormalizedLevenshtein
extends Object
implements NormalizedStringDistance, NormalizedStringSimilarity

This distance is computed as levenshtein distance divided by the length of the longest string. The resulting value is always in the interval [0.0 1.0] but it is not a metric anymore! The similarity is computed as 1 - normalized distance.

Author:

Thibault Debatty

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
NormalizedLevenshtein()

Method Summary

Methods

Modifier and Type	Method and Description
double	distance(String s1, String s2) Compute distance as Levenshtein(s1, s2) / max(|s1|, |s2|).
double	similarity(String s1, String s2) Return 1 - distance.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

NormalizedLevenshtein

public NormalizedLevenshtein()

Method Detail

distance

public final double distance(String s1,
              String s2)

Compute distance as Levenshtein(s1, s2) / max(|s1|, |s2|).

Specified by:

distance in interface StringDistance

Parameters:

s1 - The first string to compare.

s2 - The second string to compare.

Returns:

The computed distance in the range [0, 1]

Throws:

NullPointerException - if s1 or s2 is null.

similarity

public final double similarity(String s1,
                String s2)

Return 1 - distance.

Specified by:

similarity in interface StringSimilarity

Parameters:

s1 - The first string to compare.

s2 - The second string to compare.

Returns:

1.0 - the computed distance

Throws:

NullPointerException - if s1 or s2 is null.