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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Work logged] (TEXT-126) Dice's Coefficient Algorithm in String similarity
Date Sun, 24 Mar 2019 14:25:00 GMT

     [ https://issues.apache.org/jira/browse/TEXT-126?focusedWorklogId=217712&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-217712
]

ASF GitHub Bot logged work on TEXT-126:
---------------------------------------

                Author: ASF GitHub Bot
            Created on: 24/Mar/19 14:24
            Start Date: 24/Mar/19 14:24
    Worklog Time Spent: 10m 
      Work Description: aherbert commented on pull request #103: TEXT-126: Adding Sorensen-Dice
similarity algoritham
URL: https://github.com/apache/commons-text/pull/103#discussion_r268436182
 
 

 ##########
 File path: src/main/java/org/apache/commons/text/similarity/SorensenDiceSimilarity.java
 ##########
 @@ -0,0 +1,146 @@
+/*
+ * 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.ArrayList;
+import java.util.Collection;
+import java.util.List;
+import java.util.function.Function;
+
+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> {
+
+    /**
+     * For shifting bigrams to fit in single integer.
+     */
+    private static final int SHIFT_NUMBER = 16;
+
+    /**
+     * Converter function for conversion of string to bigrams.
+     */
+    private final Function<CharSequence, Collection<Integer>> converter = new
SorensenDiceConverter();
+
+    /**
+     * Measures the overlap of two sets created from a pair of character sequences.
+     * {@link OverlapSimilarity}}
+     */
+    private final IntersectionSimilarity<Integer> similarity = new IntersectionSimilarity<>(this.converter);
+
+    /**
+     * 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)) {
+            return 1d;
+        }
+
+        // if bigram is not formed out of any given string, clearly both are not similar.
+        if (left.length() < 2 || right.length() < 2) {
+            return 0d;
+        }
+
+        IntersectionResult overlap = similarity.apply(left, right);
+
+        final int total = overlap.getSizeA() + overlap.getSizeB();
+        final long intersection = overlap.getIntersection();
+
+        return (2.0d * intersection) / total;
+    }
+
+    /**
+     * Converter class for creating Bigrams for SorensenDice similarity.
+     */
+    private static class SorensenDiceConverter implements Function<CharSequence, Collection<Integer>>
{
 
 Review comment:
   This can be a singleton. No need to instantiate it for each use.
   
   `private static final SorensenDiceConverter INSTANCE = new SorensenDiceConverter()`
   
   But this functionality could also be delivered by using a method reference. It is also
not related to SorensenDice and should be in a package level utils class something like:
   
   ```
   CharSequenceConverterUtils ...
   
   List<Character> toCharacterList(CharSequence cs);
   List<Integer> toBigramList(CharSequence cs);
   List<String> toNGramList(CharSequence cs, int n);
   ```
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 217712)
    Time Spent: 14h 10m  (was: 14h)

> Dice's Coefficient Algorithm in String similarity
> -------------------------------------------------
>
>                 Key: TEXT-126
>                 URL: https://issues.apache.org/jira/browse/TEXT-126
>             Project: Commons Text
>          Issue Type: Improvement
>            Reporter: Vicky Chawda
>            Priority: Major
>          Time Spent: 14h 10m
>  Remaining Estimate: 0h
>
> I'd like to propose an extension to the algorithms for string similarity in *commons-text/src/main/java/org/apache/commons/text/similarity/*
>  Dice's Coefficient Algorithm can be helpful for many who are looking for ranking similarities
in strings.
> *Inspired from* - [http://www.catalysoft.com/articles/StrikeAMatch.html]



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