info.debatty.java.stringsimilarity

Class QGram

java.lang.Object

info.debatty.java.stringsimilarity.QGram

All Implemented Interfaces:

StringDistance, Serializable

@Immutable
public class QGram
extends Object
implements StringDistance

Q-gram distance, as defined by Ukkonen in "Approximate string-matching with q-grams and maximal matches". The distance between two strings is defined as the L1 norm of the difference of their profiles (the number of occurences of each n-gram): SUM( |V1_i - V2_i| ). Q-gram distance is a lower bound on Levenshtein distance, but can be computed in O(m + n), where Levenshtein requires O(m.n).

Author:

Thibault Debatty

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
QGram() Q-gram similarity and distance.
QGram(int k) Q-gram similarity and distance.

Method Summary

Modifier and Type	Method and Description
double	distance(Map<String,Integer> profile1, Map<String,Integer> profile2) Compute QGram distance using precomputed profiles.
double	distance(String s1, String s2) The distance between two strings is defined as the L1 norm of the difference of their profiles (the number of occurence of each k-shingle).
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".

Methods inherited from class java.lang.Object

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

Constructor Detail

QGram

public QGram(int k)

Q-gram similarity and distance. Defined by Ukkonen in "Approximate string-matching with q-grams and maximal matches", http://www.sciencedirect.com/science/article/pii/0304397592901434 The distance between two strings is defined as the L1 norm of the difference of their profiles (the number of occurences of each k-shingle). Q-gram distance is a lower bound on Levenshtein distance, but can be computed in O(|A| + |B|), where Levenshtein requires O(|A|.|B|)

Parameters:

k -

QGram

public QGram()

Q-gram similarity and distance. Defined by Ukkonen in "Approximate string-matching with q-grams and maximal matches", http://www.sciencedirect.com/science/article/pii/0304397592901434 The distance between two strings is defined as the L1 norm of the difference of their profiles (the number of occurence of each k-shingle). Q-gram distance is a lower bound on Levenshtein distance, but can be computed in O(|A| + |B|), where Levenshtein requires O(|A|.|B|) Default k is 3.

Method Detail

distance

public final double distance(String s1,
                             String s2)

The distance between two strings is defined as the L1 norm of the difference of their profiles (the number of occurence of each k-shingle).

Specified by:

distance in interface StringDistance

Parameters:

s1 - The first string to compare.

s2 - The second string to compare.

Returns:

The computed Q-gram distance.

Throws:

NullPointerException - if s1 or s2 is null.

distance

public final double distance(Map<String,Integer> profile1,
                             Map<String,Integer> profile2)

Compute QGram distance using precomputed profiles.

Parameters:

profile1 -

profile2 -

Returns:

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