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Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity...
package info.debatty.java.stringsimilarity;
import java.util.Arrays;
/**
*
* @author tibo
*/
public class JaroWinkler implements StringSimilarityInterface {
public static void main(String[] args) {
JaroWinkler jw = new JaroWinkler();
System.out.println(jw.distance("My string", "My $tring"));
System.out.println(jw.similarity("My string", "My $tring"));
}
/**
* Jaro-Winkler is string edit distance that was developed in the area of
* record linkage (duplicate detection) (Winkler, 1990).
*
* The Jaro–Winkler distance metric is designed and best suited for short
* strings such as person names, and to detect typos.
*
* http://en.wikipedia.org/wiki/Jaro-Winkler_distance
*
* @param s0
* @param s1
* @return
*/
public static double Similarity(String s0, String s1) {
JaroWinkler jw = new JaroWinkler();
return jw.similarity(s0, s1);
}
private double threshold = 0.7;
public JaroWinkler() {
}
public JaroWinkler(double threshold) {
this.setThreshold(threshold);
}
@Override
public double similarity(String s1, String s2) {
int[] mtp = matches(s1, s2);
float m = mtp[0];
if (m == 0) {
return 0f;
}
float j = ((m / s1.length() + m / s2.length() + (m - mtp[1]) / m)) / 3;
float jw = j < getThreshold() ? j : j + Math.min(0.1f, 1f / mtp[3]) * mtp[2]
* (1 - j);
return jw;
}
@Override
public double distance(String s1, String s2) {
return 1.0 - similarity(s1, s2);
}
/**
* Sets the threshold used to determine when Winkler bonus should be used.
* Set to a negative value to get the Jaro distance.
* Default value is 0.7
*
* @param threshold the new value of the threshold
*/
public final void setThreshold(double threshold) {
this.threshold = threshold;
}
/**
* Returns the current value of the threshold used for adding the Winkler
* bonus. The default value is 0.7.
*
* @return the current value of the threshold
*/
public double getThreshold() {
return threshold;
}
private int[] matches(String s1, String s2) {
String max, min;
if (s1.length() > s2.length()) {
max = s1;
min = s2;
} else {
max = s2;
min = s1;
}
int range = Math.max(max.length() / 2 - 1, 0);
int[] matchIndexes = new int[min.length()];
Arrays.fill(matchIndexes, -1);
boolean[] matchFlags = new boolean[max.length()];
int matches = 0;
for (int mi = 0; mi < min.length(); mi++) {
char c1 = min.charAt(mi);
for (int xi = Math.max(mi - range, 0),
xn = Math.min(mi + range + 1, max.length()); xi < xn; xi++) {
if (!matchFlags[xi] && c1 == max.charAt(xi)) {
matchIndexes[mi] = xi;
matchFlags[xi] = true;
matches++;
break;
}
}
}
char[] ms1 = new char[matches];
char[] ms2 = new char[matches];
for (int i = 0, si = 0; i < min.length(); i++) {
if (matchIndexes[i] != -1) {
ms1[si] = min.charAt(i);
si++;
}
}
for (int i = 0, si = 0; i < max.length(); i++) {
if (matchFlags[i]) {
ms2[si] = max.charAt(i);
si++;
}
}
int transpositions = 0;
for (int mi = 0; mi < ms1.length; mi++) {
if (ms1[mi] != ms2[mi]) {
transpositions++;
}
}
int prefix = 0;
for (int mi = 0; mi < min.length(); mi++) {
if (s1.charAt(mi) == s2.charAt(mi)) {
prefix++;
} else {
break;
}
}
return new int[]{matches, transpositions / 2, prefix, max.length()};
}
}