Source code
Description: source: package: org.apache.commons.text.similarity, class: JaroWinklerSimilarity

    001/*
    002 * Licensed to the Apache Software Foundation (ASF) under one or more
    003 * contributor license agreements.  See the NOTICE file distributed with
    004 * this work for additional information regarding copyright ownership.
    005 * The ASF licenses this file to You under the Apache License, Version 2.0
    006 * (the "License"); you may not use this file except in compliance with
    007 * the License.  You may obtain a copy of the License at
    008 *
    009 *      http://www.apache.org/licenses/LICENSE-2.0
    010 *
    011 * Unless required by applicable law or agreed to in writing, software
    012 * distributed under the License is distributed on an "AS IS" BASIS,
    013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    014 * See the License for the specific language governing permissions and
    015 * limitations under the License.
    016 */
    017package org.apache.commons.text.similarity;
    018
    019import java.util.Arrays;
    020
    021import org.apache.commons.lang3.StringUtils;
    022
    023/**
    024 * A similarity algorithm indicating the percentage of matched characters between two character sequences.
    025 *
    026 * <p>
    027 * The Jaro measure is the weighted sum of percentage of matched characters
    028 * from each file and transposed characters. Winkler increased this measure
    029 * for matching initial characters.
    030 * </p>
    031 *
    032 * <p>
    033 * This implementation is based on the Jaro Winkler similarity algorithm
    034 * from <a href="http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance">
    035 * http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance</a>.
    036 * </p>
    037 *
    038 * <p>
    039 * This code has been adapted from Apache Commons Lang 3.3.
    040 * </p>
    041 *
    042 * @since 1.7
    043 */
    044public class JaroWinklerSimilarity implements SimilarityScore<Double> {
    045
    046    /**
    047     * Singleton instance.
    048     */
    049    static final JaroWinklerSimilarity INSTANCE = new JaroWinklerSimilarity();
    050
    051    /**
    052     * This method returns the Jaro-Winkler string matches, half transpositions, prefix array.
    053     *
    054     * @param first the first string to be matched
    055     * @param second the second string to be matched
    056     * @return mtp array containing: matches, half transpositions, and prefix
    057     */
    058    protected static int[] matches(final CharSequence first, final CharSequence second) {
    059        final CharSequence max;
    060        final CharSequence min;
    061        if (first.length() > second.length()) {
    062            max = first;
    063            min = second;
    064        } else {
    065            max = second;
    066            min = first;
    067        }
    068        final int range = Math.max(max.length() / 2 - 1, 0);
    069        final int[] matchIndexes = new int[min.length()];
    070        Arrays.fill(matchIndexes, -1);
    071        final boolean[] matchFlags = new boolean[max.length()];
    072        int matches = 0;
    073        for (int mi = 0; mi < min.length(); mi++) {
    074            final char c1 = min.charAt(mi);
    075            for (int xi = Math.max(mi - range, 0), xn = Math.min(mi + range + 1, max.length()); xi < xn; xi++) {
    076                if (!matchFlags[xi] && c1 == max.charAt(xi)) {
    077                    matchIndexes[mi] = xi;
    078                    matchFlags[xi] = true;
    079                    matches++;
    080                    break;
    081                }
    082            }
    083        }
    084        final char[] ms1 = new char[matches];
    085        final char[] ms2 = new char[matches];
    086        for (int i = 0, si = 0; i < min.length(); i++) {
    087            if (matchIndexes[i] != -1) {
    088                ms1[si] = min.charAt(i);
    089                si++;
    090            }
    091        }
    092        for (int i = 0, si = 0; i < max.length(); i++) {
    093            if (matchFlags[i]) {
    094                ms2[si] = max.charAt(i);
    095                si++;
    096            }
    097        }
    098        int halfTranspositions = 0;
    099        for (int mi = 0; mi < ms1.length; mi++) {
    100            if (ms1[mi] != ms2[mi]) {
    101                halfTranspositions++;
    102            }
    103        }
    104        int prefix = 0;
    105        for (int mi = 0; mi < Math.min(4, min.length()); mi++) {
    106            if (first.charAt(mi) != second.charAt(mi)) {
    107                break;
    108            }
    109            prefix++;
    110        }
    111        return new int[] {matches, halfTranspositions, prefix};
    112    }
    113
    114    /**
    115     * Computes the Jaro Winkler Similarity between two character sequences.
    116     *
    117     * <pre>
    118     * sim.apply(null, null)          = IllegalArgumentException
    119     * sim.apply("foo", null)         = IllegalArgumentException
    120     * sim.apply(null, "foo")         = IllegalArgumentException
    121     * sim.apply("", "")              = 1.0
    122     * sim.apply("foo", "foo")        = 1.0
    123     * sim.apply("foo", "foo ")       = 0.94
    124     * sim.apply("foo", "foo  ")      = 0.91
    125     * sim.apply("foo", " foo ")      = 0.87
    126     * sim.apply("foo", "  foo")      = 0.51
    127     * sim.apply("", "a")             = 0.0
    128     * sim.apply("aaapppp", "")       = 0.0
    129     * sim.apply("frog", "fog")       = 0.93
    130     * sim.apply("fly", "ant")        = 0.0
    131     * sim.apply("elephant", "hippo") = 0.44
    132     * sim.apply("hippo", "elephant") = 0.44
    133     * sim.apply("hippo", "zzzzzzzz") = 0.0
    134     * sim.apply("hello", "hallo")    = 0.88
    135     * sim.apply("ABC Corporation", "ABC Corp") = 0.91
    136     * sim.apply("D N H Enterprises Inc", "D &amp; H Enterprises, Inc.") = 0.95
    137     * sim.apply("My Gym Children's Fitness Center", "My Gym. Childrens Fitness") = 0.92
    138     * sim.apply("PENNSYLVANIA", "PENNCISYLVNIA") = 0.88
    139     * </pre>
    140     *
    141     * @param left the first CharSequence, must not be null
    142     * @param right the second CharSequence, must not be null
    143     * @return result similarity
    144     * @throws IllegalArgumentException if either CharSequence input is {@code null}
    145     */
    146    @Override
    147    public Double apply(final CharSequence left, final CharSequence right) {
    148        final double defaultScalingFactor = 0.1;
    149
    150        if (left == null || right == null) {
    151            throw new IllegalArgumentException("CharSequences must not be null");
    152        }
    153
    154        if (StringUtils.equals(left, right)) {
    155            return 1d;
    156        }
    157
    158        final int[] mtp = matches(left, right);
    159        final double m = mtp[0];
    160        if (m == 0) {
    161            return 0d;
    162        }
    163        final double j = (m / left.length() + m / right.length() + (m - (double) mtp[1] / 2) / m) / 3;
    164        return j < 0.7d ? j : j + defaultScalingFactor * mtp[2] * (1d - j);
    165    }
    166
    167}