Added SorensenDice coefficient

Author: tdebatty

src/main/java/info/debatty/java/stringsimilarity/Jaccard.java

@@ -43,7 +43,7 @@ public static void main(String[] args) {
         System.out.println(j2.similarity("ABCDE", "ABCDF"));
     }
 
-    private int k;
+    private final int k;
 
     /**
      * The strings are first transformed into sets of k-shingles (sequences of k

src/main/java/info/debatty/java/stringsimilarity/QGram.java

@@ -31,14 +31,14 @@ public static void main(String[] args) {
                 "High Qua1ityMedications   Discount On All Reorders = Best Deal Ever! Viagra50/100mg - $1.85 7z3"));
     }
 
-    private int n;
+    private final int k;
 
     public QGram(int n) {
-        this.n = n;
+        this.k = n;
     }
 
     public QGram() {
-        this.n = 3;
+        this.k = 3;
     }
 
     @Override
@@ -56,11 +56,11 @@ public int absoluteDistance(String s1, String s2) {
     }
 
     protected double dist(String s1, String s2, boolean abs) {
-        if (s1.length() < n || s2.length() < n) {
+        if (s1.length() < k || s2.length() < k) {
             return 1;
         }
 
-        KShingling sh = new KShingling(n);
+        KShingling sh = new KShingling(k);
         sh.parse(s1);
         sh.parse(s2);
 

src/main/java/info/debatty/java/stringsimilarity/SorensenDice.java

@@ -0,0 +1,102 @@
+/*
+ * The MIT License
+ *
+ * Copyright 2015 tibo.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+package info.debatty.java.stringsimilarity;
+
+/**
+ * Sorensen-Dice coefficien, aka Sørensen index, Dice's coefficient or 
+ * Czekanowski's binary (non-quantitative) index.
+ * 
+ * The strings are first converted to boolean sets of k-shingles (strings of k
+ * characters), then the similarity is computed as 2 |A inter B| / (|A| + |B|).
+ * Attention: Sorensen-Dice distance (and similarity) does not satisfy 
+ * triangle inequality.
+ * 
+ * @author Thibault Debatty
+ */
+public class SorensenDice implements StringSimilarityInterface {
+
+    /**
+     * @param args the command line arguments
+     */
+    public static void main(String[] args) {
+        SorensenDice sd = new SorensenDice(2);
+        
+        // AB BC CD DE DF FG
+        // 1  1  1  1  0  0
+        // 1  1  1  0  1  1
+        // => 2 x 3 / (4 + 5) = 6/9 = 0.6666
+        System.out.println(sd.similarity("ABCDE", "ABCDFG"));
+    }
+
+    private final int k;
+    
+    public SorensenDice(int k) {
+        this.k = k;
+    }
+    
+    public SorensenDice() {
+        this.k = 3;
+    }
+    
+    /**
+     * Compute Sorensen-Dice coefficient 2 |A inter B| / (|A| + |B|).
+     * @param s1
+     * @param s2
+     * @return 
+     */
+    public double similarity(String s1, String s2) {
+        KShingling ks = new KShingling(this.k);
+        
+        ks.parse(s1);
+        ks.parse(s2);
+        
+        boolean[] v1 = ks.booleanVectorOf(s1);
+        boolean[] v2 = ks.booleanVectorOf(s2);
+        
+        int inter = 0;
+        int sum = 0;
+        for (int i = 0; i < v1.length; i++) {
+            if (v1[i] && v2[i]) {
+                inter++;
+            }
+            
+            if (v1[i]) {
+                sum++;
+            }
+            
+            if (v2[i]) {
+                sum++;
+            }
+        }
+        
+        return 2.0 * inter / sum;
+        
+    }
+
+    public double distance(String s1, String s2) {
+        return 1.0 - similarity(s1, s2);
+    }
+    
+}