Skip to content

TEXT-126: Adding Sorensen-Dice similarity algoritham #103

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 20 commits into from
Closed
Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
20 commits
Select commit Hold shift + click to select a range
7aae02b
Adding Sorensen-Dice similarity algoritham
ameyjadiye Feb 26, 2019
325658b
added documentation and optimised code
ameyjadiye Feb 27, 2019
4191840
replacing bit faster version of empty check
ameyjadiye Mar 1, 2019
9070f05
Improved javadocs and handled some edge cases
ameyjadiye Mar 3, 2019
505066c
TEXT-155: Add a generic IntersectionSimilarity measure
aherbert Mar 7, 2019
8b92150
TEXT-155: Add a generic IntersectionSimilarity measure
aherbert Mar 7, 2019
0ebc77f
Merge branch 'feature-TEXT-155' of
aherbert Mar 8, 2019
0c66921
TEXT-155: IntersectionSimilarity to support duplicates in union.
aherbert Mar 8, 2019
dae816a
TEXT-155: Add word letter pairs test to IntersectionSimilarityTest
aherbert Mar 8, 2019
ae21c63
Text-155: Javadoc fix in IntersectionResult
aherbert Mar 8, 2019
9a7d018
TEXT-155: Renamed to OverlapSimilarity.
aherbert Mar 9, 2019
af9ed62
Merge pull request #1 from apache/master
ameyjadiye Mar 10, 2019
6344be4
Merge pull request #2 from aherbert/feature-TEXT-155
ameyjadiye Mar 10, 2019
7a4aee8
using OverlapSimilarity for scoring Sorensendice similarity
ameyjadiye Mar 10, 2019
211077b
rounded resulring scores for tests
ameyjadiye Mar 10, 2019
29fd2da
fixed spotbug checkstyle errors
ameyjadiye Mar 10, 2019
0d77d4e
Merge pull request #3 from apache/master
ameyjadiye Mar 13, 2019
bcff974
no need
ameyjadiye Mar 18, 2019
2de106e
using new IntersectionSimilarity
ameyjadiye Mar 18, 2019
8f0a97c
corrected javadoc, removed unused code and made instance var private.
ameyjadiye Mar 24, 2019
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Original file line number Diff line number Diff line change
@@ -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;
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Not part of this class but the internal converter class.


/**
* 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>> {
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

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);

@Override
public Collection<Integer> apply(CharSequence cs) {
final int length = cs.length();
final List<Integer> list = new ArrayList<>(length);
if (length > 1) {
char ch2 = cs.charAt(0);
for (int i = 1; i < length; i++) {
final char ch1 = ch2;
ch2 = cs.charAt(i);
list.add(Integer.valueOf((ch1 << SHIFT_NUMBER) | ch2));
}
}
return list;
}
}
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,94 @@
/*
* 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 static org.assertj.core.api.Assertions.assertThatIllegalArgumentException;
import static org.junit.jupiter.api.Assertions.assertEquals;

import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;

/**
* Unit tests for {@link SorensenDicesSimilarity}.
*/
public class SorensenDiceSimilarityTest {

private static SorensenDiceSimilarity similarity;

@BeforeAll
public static void setUp() {
similarity = new SorensenDiceSimilarity();
}

@Test
public void test() {
assertEquals(0.25d, similarity.apply("night", "nacht"));
}

@Test
public void testGetSorensenDicesSimilarity_StringString() {

assertEquals(1d, similarity.apply("", ""));
assertEquals(0d, similarity.apply("", "a"));
assertEquals(0d, similarity.apply("a", ""));
assertEquals(1d, similarity.apply("a", "a"));
assertEquals(0d, similarity.apply("a", "b"));
assertEquals(1.0d, similarity.apply("foo", "foo"));
assertEquals(0.8d, similarity.apply("foo", "foo "));
assertEquals(0.4d, similarity.apply("frog", "fog"));
assertEquals(0.0d, similarity.apply("fly", "ant"));
assertEquals(0.0d, similarity.apply("elephant", "hippo"));
assertEquals(0.0d, similarity.apply("hippo", "elephant"));
assertEquals(0.0d, similarity.apply("hippo", "zzzzzzzz"));
assertEquals(0.5d, similarity.apply("hello", "hallo"));
assertEquals(0.7d, round(similarity.apply("ABC Corporation", "ABC Corp"), 1));
assertEquals(0.7d, round(similarity.apply("D N H Enterprises Inc", "D &amp; H Enterprises, Inc."), 1));
assertEquals(0.8d,
round(similarity.apply("My Gym Children's Fitness Center", "My Gym. Childrens Fitness"), 1));
assertEquals(0.7d, round(similarity.apply("PENNSYLVANIA", "PENNCISYLVNIA"), 1));
assertEquals(0.9d, round(similarity.apply("/opt/software1", "/opt/software2"), 1));
assertEquals(0.6d, round(similarity.apply("aaabcd", "aaacdb"), 1));
assertEquals(0.6d, round(similarity.apply("John Horn", "John Hopkins"), 1));

}

@Test
public void testGetSorensenDicesSimilarity_NullNull() {
assertThatIllegalArgumentException().isThrownBy(() -> {
similarity.apply(null, null);
});
}

@Test
public void testGetSorensenDicesSimilarity_StringNull() {
assertThatIllegalArgumentException().isThrownBy(() -> {
similarity.apply(" ", null);
});
}

@Test
public void testGetSorensenDicesSimilarity_NullString() {
assertThatIllegalArgumentException().isThrownBy(() -> {
similarity.apply(null, "clear");
});
}

public static double round(double value, int precision) {
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

No need to be public. Why are you rounding anyway? A test like this can be very precise.

int scale = (int) Math.pow(10, precision);
return (double) Math.round(value * scale) / scale;
}
}