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Subject [GitHub] [commons-text] ameyjadiye commented on a change in pull request #103: TEXT-126: Adding Sorensen-Dice similarity algoritham
Date Sat, 09 Mar 2019 06:16:53 GMT
ameyjadiye commented on a change in pull request #103: TEXT-126: Adding Sorensen-Dice similarity
algoritham
URL: https://github.com/apache/commons-text/pull/103#discussion_r263988419
 
 

 ##########
 File path: src/main/java/org/apache/commons/text/similarity/SorensenDiceSimilarity.java
 ##########
 @@ -0,0 +1,127 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.commons.text.similarity;
+
+import java.util.HashSet;
+import java.util.Set;
+import java.util.stream.Collectors;
+
+import org.apache.commons.lang3.StringUtils;
+
+/**
+ * A similarity algorithm indicating the percentage of matched characters
+ * between two character sequences.
+ *
+ * <p>
+ * The S&#248;rensen–Dice coefficient is a statistic used for comparing the
+ * similarity of two samples. It was independently developed by the botanists
+ * Thorvald S&#248;rensen and Lee Raymond Dice, who published in 1948 and 1945
+ * respectively. The index is known by several other names, especially
+ * S&#248;rensen–Dice index, S&#248;rensen index and Dice's coefficient. Other
+ * variations include the "similarity coefficient" or "index", such as Dice
+ * similarity coefficient (DSC).
+ * </p>
+ *
+ * <p>
+ * This implementation is based on the S&#248;rensen–Dice similarity algorithm
+ * from <a href=
+ * "http://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient">
+ * http://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient</a>.
+ *
+ *
+ * </p>
+ *
+ * @since 1.7
+ */
+public class SorensenDiceSimilarity implements SimilarityScore<Double> {
+
+    /**
+     * Calculates Sorensen-Dice Similarity of two character sequences passed as
+     * input.
+     *
+     * <pre>
+     * similarity.apply(null, null)                 = IllegalArgumentException
+     * similarity.apply("foo", null)                = IllegalArgumentException
+     * similarity.apply(null, "foo")                = IllegalArgumentException
+     * similarity.apply("night", "nacht")           = 0.25
+     * similarity.apply("", "")                     = 1.0
+     * similarity.apply("foo", "foo")               = 1.0
+     * similarity.apply("foo", "foo ")              = 0.8
+     * similarity.apply("foo", "foo ")              = 0.66
+     * similarity.apply("foo", " foo ")             = 0.66
+     * similarity.apply("foo", " foo")              = 0.66
+     * similarity.apply("", "a")                    = 0.0
+     * similarity.apply("aaapppp", "")              = 0.0
+     * similarity.apply("frog", "fog")              = 0.4
+     * similarity.apply("fly", "ant")               = 0.0
+     * similarity.apply("elephant", "hippo")        = 0.0
+     * similarity.apply("hippo", "elephant")        = 0.0
+     * similarity.apply("hippo", "zzzzzzzz")        = 0.0
+     * similarity.apply("hello", "hallo")           = 0.5
+     * similarity.apply("ABC Corporation", "ABC Corp") = 0.7
+     * similarity.apply("D N H Enterprises Inc", "D &amp; H Enterprises, Inc.") = 0.74
+     * similarity.apply("My Gym Children's Fitness Center", "My Gym. Childrens Fitness")
= 0.81
+     * similarity.apply("PENNSYLVANIA", "PENNCISYLVNIA") = 0.69
+     * </pre>
+     *
+     * @param left  the first CharSequence, must not be null
+     * @param right the second CharSequence, must not be null
+     * @return result similarity
+     * @throws IllegalArgumentException if either CharSequence input is {@code null}
+     */
+    @Override
+    public Double apply(final CharSequence left, final CharSequence right) {
+
+        if (left == null || right == null) {
+            throw new IllegalArgumentException("CharSequences must not be null");
+        }
+
+        if (StringUtils.equals(left, right)) {
 
 Review comment:
   
   ```
   >>> 1 - jellyfish.levenshtein_distance(u'a', u'a')
   1
   >>> 
   >>> 1 - jellyfish.levenshtein_distance(u'', u'')
   1
   ```
   
   _Note -  similarity  = 1 - distance_ 

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