info.debatty.java.stringsimilarity

Class Jaccard

java.lang.Object

info.debatty.java.stringsimilarity.Jaccard

All Implemented Interfaces:

MetricStringDistance, NormalizedStringDistance, NormalizedStringSimilarity, StringDistance, StringSimilarity, Serializable

@Immutable
public class Jaccard
extends Object
implements MetricStringDistance, NormalizedStringDistance, NormalizedStringSimilarity

Each input string is converted into a set of n-grams, the Jaccard index is then computed as |V1 inter V2| / |V1 union V2|. Like Q-Gram distance, the input strings are first converted into sets of n-grams (sequences of n characters, also called k-shingles), but this time the cardinality of each n-gram is not taken into account. Distance is computed as 1 - cosine similarity. Jaccard index is a metric distance.

Author:

Thibault Debatty

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Jaccard() The strings are first transformed into sets of k-shingles (sequences of k characters), then Jaccard index is computed as |A inter B| / |A union B|.
Jaccard(int k) The strings are first transformed into sets of k-shingles (sequences of k characters), then Jaccard index is computed as |A inter B| / |A union B|.

Method Summary

Modifier and Type	Method and Description
double	distance(String s1, String s2) Distance is computed as 1 - similarity.
int	getK() Return k, the length of k-shingles (aka n-grams).
Map<String,Integer>	getProfile(String string) Compute and return the profile of s, as defined by Ukkonen "Approximate string-matching with q-grams and maximal matches".
double	similarity(String s1, String s2) Compute Jaccard index: |A inter B| / |A union B|.

Methods inherited from class java.lang.Object

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

Constructor Detail

Jaccard

public Jaccard(int k)

The strings are first transformed into sets of k-shingles (sequences of k characters), then Jaccard index is computed as |A inter B| / |A union B|. The default value of k is 3.

Parameters:

k -

Jaccard

public Jaccard()

The strings are first transformed into sets of k-shingles (sequences of k characters), then Jaccard index is computed as |A inter B| / |A union B|. The default value of k is 3.

Method Detail

similarity

public final double similarity(String s1,
                               String s2)

Compute Jaccard index: |A inter B| / |A union B|.

Specified by:

similarity in interface StringSimilarity

Parameters:

s1 - The first string to compare.

s2 - The second string to compare.

Returns:

The Jaccard index in the range [0, 1]

Throws:

NullPointerException - if s1 or s2 is null.

distance

public final double distance(String s1,
                             String s2)

Distance is computed as 1 - similarity.

Specified by:

distance in interface MetricStringDistance

Specified by:

distance in interface StringDistance

Parameters:

s1 - The first string to compare.

s2 - The second string to compare.

Returns:

1 - the Jaccard similarity.

Throws:

NullPointerException - if s1 or s2 is null.

getK

public int getK()

Return k, the length of k-shingles (aka n-grams).

Returns:

The length of k-shingles.

getProfile

public final Map<String,Integer> getProfile(String string)

Compute and return the profile of s, as defined by Ukkonen "Approximate string-matching with q-grams and maximal matches". https://www.cs.helsinki.fi/u/ukkonen/TCS92.pdf The profile is the number of occurrences of k-shingles, and is used to compute q-gram similarity, Jaccard index, etc. Pay attention: the memory requirement of the profile can be up to k * size of the string

Parameters:

string -

Returns:

the profile of this string, as an unmodifiable Map