info.debatty.java.stringsimilarity

Class Cosine

java.lang.Object

info.debatty.java.stringsimilarity.Cosine

All Implemented Interfaces:

NormalizedStringDistance, NormalizedStringSimilarity, StringDistance, StringSimilarity, Serializable

public class Cosine
extends Object
implements NormalizedStringDistance, NormalizedStringSimilarity

The similarity between the two strings is the cosine of the angle between these two vectors representation. It is computed as V1 . V2 / (|V1| * |V2|) The cosine distance is computed as 1 - cosine similarity.

Author:

Thibault Debatty

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected int	k

Constructor Summary

Constructors

Constructor and Description
Cosine()
Cosine(int k) Implements Cosine Similarity between strings.

Method Summary

Methods

Modifier and Type	Method and Description
double	distance(String s1, String s2) Return 1.0 - similarity.
protected static double	dotProduct(int[] profile1, int[] profile2)
int	getK() Return k, the length of k-shingles (aka n-grams)
protected static double	norm(int[] profile) Compute the norm L2 : sqrt(Sum_i( v_i²)).
double	similarity(String s1, String s2) Compute the cosine similarity between strings.

Methods inherited from class java.lang.Object

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

Field Detail

k

protected final int k

Constructor Detail

Cosine

public Cosine(int k)

Implements Cosine Similarity between strings. The strings are first transformed in vectors of occurrences of k-shingles (sequences of k characters). In this n-dimensional space, the similarity between the two strings is the cosine of their respective vectors.

Parameters:

k -

Cosine

public Cosine()

Method Detail

similarity

public final double similarity(String s1,
                String s2)

Compute the cosine similarity between strings.

Specified by:

similarity in interface StringSimilarity

Parameters:

s1 -

s2 -

Returns:

norm

protected static double norm(int[] profile)

Compute the norm L2 : sqrt(Sum_i( v_i²)).

Parameters:

profile -

Returns:

L2 norm

dotProduct

protected static double dotProduct(int[] profile1,
                int[] profile2)

distance

public final double distance(String s1,
              String s2)

Return 1.0 - similarity.

Specified by:

distance in interface StringDistance

Parameters:

s1 -

s2 -

Returns:

getK

public int getK()

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

Returns: