[GitHub] kinow commented on a change in pull request #100: TEXT-104: Jaro Winkler Distance refers to similarity

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kinow commented on a change in pull request #100: TEXT-104: Jaro Winkler Distance refers to similarity
URL: https://github.com/apache/commons-text/pull/100#discussion_r257453758
 
 

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 File path: src/main/java/org/apache/commons/text/similarity/JaroWinklerSimilarity.java
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+/*
+ * 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.Arrays;
+
+/**
+ * A similarity algorithm indicating the percentage of matched characters between two character sequences.
+ *
+ * <p>
+ * The Jaro measure is the weighted sum of percentage of matched characters
+ * from each file and transposed characters. Winkler increased this measure
+ * for matching initial characters.
+ * </p>
+ *
+ * <p>
+ * This implementation is based on the Jaro Winkler similarity algorithm
+ * from <a href="http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance">
+ * http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance</a>.
+ * </p>
+ *
+ * <p>
+ * This code has been adapted from Apache Commons Lang 3.3.
+ * </p>
+ *
+ * @since 1.7
+ */
+public class JaroWinklerSimilarity implements SimilarityScore<Double> {
+
+    /**
+     * Computes the Jaro Winkler Similarity between two character sequences.
+     *
+     * <pre>
+     * sim.apply(null, null)          = IllegalArgumentException
+     * sim.apply("foo", null)         = IllegalArgumentException
+     * sim.apply(null, "foo")         = IllegalArgumentException
+     * sim.apply("", "")              = 1.0
+     * sim.apply("foo", "foo")        = 1.0
+     * sim.apply("foo", "foo ")       = 0.94
+     * sim.apply("foo", "foo  ")      = 0.91
+     * sim.apply("foo", " foo ")      = 0.87
+     * sim.apply("foo", "  foo")      = 0.51
+     * sim.apply("", "a")             = 0.0
+     * sim.apply("aaapppp", "")       = 0.0
+     * sim.apply("frog", "fog")       = 0.93
+     * sim.apply("fly", "ant")        = 0.0
+     * sim.apply("elephant", "hippo") = 0.44
+     * sim.apply("hippo", "elephant") = 0.44
+     * sim.apply("hippo", "zzzzzzzz") = 0.0
+     * sim.apply("hello", "hallo")    = 0.88
+     * sim.apply("ABC Corporation", "ABC Corp") = 0.93
+     * sim.apply("D N H Enterprises Inc", "D &amp; H Enterprises, Inc.") = 0.95
+     * sim.apply("My Gym Children's Fitness Center", "My Gym. Childrens Fitness") = 0.92
+     * sim.apply("PENNSYLVANIA", "PENNCISYLVNIA") = 0.88
+     * </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) {
+        final double defaultScalingFactor = 0.1;
+
+        if (left == null || right == null) {
+            throw new IllegalArgumentException("CharSequences must not be null");
+        }
+
+        if (left.equals(right)) {
+            return 1D;
 
 Review comment:
   Just realized in the rest of the code we have `d` instead of `D` (e.g. `JaccardDistance.`, `CosineSimilarity`), but the old code was using `D` already. We can fix it later to have a more uniform use.

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