Package org.apache.commons.text.similarity

Class JaroWinklerSimilarity

java.lang.Object

org.apache.commons.text.similarity.JaroWinklerSimilarity

All Implemented Interfaces:

java.util.function.BiFunction<java.lang.CharSequence,java.lang.CharSequence,java.lang.Double>, ObjectSimilarityScore<java.lang.CharSequence,java.lang.Double>, SimilarityScore<java.lang.Double>

public class JaroWinklerSimilarity
extends java.lang.Object
implements SimilarityScore<java.lang.Double>

A similarity algorithm indicating the percentage of matched characters between two character sequences.

The Jaro measure is the weighted sum of percentage of matched characters from each file and transposed characters. Winkler increased this measure for matching initial characters.

This implementation is based on the Jaro Winkler similarity algorithm from https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance.

This code has been adapted from Apache Commons Lang 3.3.

Since:

1.7

Constructor Summary

Constructors

Constructor	Description
JaroWinklerSimilarity()	Creates a new instance.

Method Summary

Modifier and Type	Method	Description
java.lang.Double	apply(java.lang.CharSequence left, java.lang.CharSequence right)	Computes the Jaro Winkler Similarity between two character sequences.
<E> java.lang.Double	apply(SimilarityInput<E> left, SimilarityInput<E> right)	Computes the Jaro Winkler Similarity between two character sequences.
protected static int[]	matches(java.lang.CharSequence first, java.lang.CharSequence second)	Computes the Jaro-Winkler string matches, half transpositions, prefix array.
protected static <E> int[]	matches(SimilarityInput<E> first, SimilarityInput<E> second)	Computes the Jaro-Winkler string matches, half transpositions, prefix array.

Methods inherited from class java.lang.Object

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

Methods inherited from interface java.util.function.BiFunction

andThen

Constructor Detail

JaroWinklerSimilarity

public JaroWinklerSimilarity()

Creates a new instance.

Method Detail

matches

protected static int[] matches(java.lang.CharSequence first,
                               java.lang.CharSequence second)

Computes the Jaro-Winkler string matches, half transpositions, prefix array.

Parameters:

first - the first input to be matched.

second - the second input to be matched.

Returns:

mtp array containing: matches, half transpositions, and prefix.

matches

protected static <E> int[] matches(SimilarityInput<E> first,
                                   SimilarityInput<E> second)

Computes the Jaro-Winkler string matches, half transpositions, prefix array.

Type Parameters:

E - The type of similarity score unit.

Parameters:

first - the first input to be matched.

second - the second input to be matched.

Returns:

mtp array containing: matches, half transpositions, and prefix.

Since:

1.13.0

apply

public java.lang.Double apply(java.lang.CharSequence left,
                              java.lang.CharSequence right)

Computes the Jaro Winkler Similarity between two character sequences.

 sim.apply(null, null)          = Throws IllegalArgumentException
 sim.apply("foo", null)         = Throws IllegalArgumentException
 sim.apply(null, "foo")         = Throws IllegalArgumentException
 sim.apply("", "")              = 1.0
 sim.apply("foo", "foo")        = 1.0
 sim.apply("foo", "foo ")       = 0.94
 sim.apply("foo", "foo  ")      = 0.91
 sim.apply("foo", " foo ")      = 0.87
 sim.apply("foo", "  foo")      = 0.51
 sim.apply("", "a")             = 0.0
 sim.apply("aaapppp", "")       = 0.0
 sim.apply("frog", "fog")       = 0.93
 sim.apply("fly", "ant")        = 0.0
 sim.apply("elephant", "hippo") = 0.44
 sim.apply("hippo", "elephant") = 0.44
 sim.apply("hippo", "zzzzzzzz") = 0.0
 sim.apply("hello", "hallo")    = 0.88
 sim.apply("ABC Corporation", "ABC Corp") = 0.91
 sim.apply("D N H Enterprises Inc", "D & H Enterprises, Inc.") = 0.95
 sim.apply("My Gym Children's Fitness Center", "My Gym. Childrens Fitness") = 0.92
 sim.apply("PENNSYLVANIA", "PENNCISYLVNIA") = 0.88
 

Specified by:

apply in interface java.util.function.BiFunction<java.lang.CharSequence,java.lang.CharSequence,java.lang.Double>

Specified by:

apply in interface ObjectSimilarityScore<java.lang.CharSequence,java.lang.Double>

Specified by:

apply in interface SimilarityScore<java.lang.Double>

Parameters:

left - the first input, must not be null.

right - the second input, must not be null.

Returns:

result similarity.

Throws:

java.lang.IllegalArgumentException - if either CharSequence input is null.

apply

public <E> java.lang.Double apply(SimilarityInput<E> left,
                                  SimilarityInput<E> right)

Computes the Jaro Winkler Similarity between two character sequences.

 sim.apply(null, null)          = Throws IllegalArgumentException
 sim.apply("foo", null)         = Throws IllegalArgumentException
 sim.apply(null, "foo")         = Throws IllegalArgumentException
 sim.apply("", "")              = 1.0
 sim.apply("foo", "foo")        = 1.0
 sim.apply("foo", "foo ")       = 0.94
 sim.apply("foo", "foo  ")      = 0.91
 sim.apply("foo", " foo ")      = 0.87
 sim.apply("foo", "  foo")      = 0.51
 sim.apply("", "a")             = 0.0
 sim.apply("aaapppp", "")       = 0.0
 sim.apply("frog", "fog")       = 0.93
 sim.apply("fly", "ant")        = 0.0
 sim.apply("elephant", "hippo") = 0.44
 sim.apply("hippo", "elephant") = 0.44
 sim.apply("hippo", "zzzzzzzz") = 0.0
 sim.apply("hello", "hallo")    = 0.88
 sim.apply("ABC Corporation", "ABC Corp") = 0.91
 sim.apply("D N H Enterprises Inc", "D & H Enterprises, Inc.") = 0.95
 sim.apply("My Gym Children's Fitness Center", "My Gym. Childrens Fitness") = 0.92
 sim.apply("PENNSYLVANIA", "PENNCISYLVNIA") = 0.88
 

Type Parameters:

E - The type of similarity score unit.

Parameters:

left - the first input, must not be null.

right - the second input, must not be null.

Returns:

result similarity.

Throws:

java.lang.IllegalArgumentException - if either CharSequence input is null.

Since:

1.13.0