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https://issues.apache.org/jira/browse/TEXT-155?focusedWorklogId=210453&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-210453
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ASF GitHub Bot logged work on TEXT-155:
---------------------------------------
Author: ASF GitHub Bot
Created on: 09/Mar/19 04:09
Start Date: 09/Mar/19 04:09
Worklog Time Spent: 10m
Work Description: kinow commented on pull request #109: TEXT-155: Add a
generic IntersectionSimilarity measure
URL: https://github.com/apache/commons-text/pull/109#discussion_r263985577
##########
File path:
src/main/java/org/apache/commons/text/similarity/IntersectionSimilarity.java
##########
@@ -0,0 +1,197 @@
+/*
+ * 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.Collection;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.Set;
+import java.util.function.Function;
+import java.util.stream.Stream;
+
+/**
+ * Measures the intersection of two sets created from a pair of character
sequences.
+ *
+ * <p>It is assumed that the type {@code T} correctly conforms to the
requirements for storage
+ * within a {@link Set} or {@link HashMap}. Ideally the type is immutable and
implements
+ * {@link Object#equals(Object)} and {@link Object#hashCode()}.</p>
+ *
+ * @param <T> the type of the elements extracted from the character sequence
+ * @since 1.7
+ * @see Set
+ * @see HashMap
+ */
+public class IntersectionSimilarity<T> implements
SimilarityScore<IntersectionResult> {
+ /** The converter used to create the elements from the characters. */
+ private final Function<CharSequence, Collection<T>> converter;
+
+ // The following is adapted from commons-collections for a Bag.
+ // A Bag is a collection that can store the count of the number
+ // of copies of each element.
+
+ /**
+ * Mutable counter class for storing the count of elements.
+ */
+ private static class BagCount {
+ /** The count. This is initialised to 1 upon construction. */
+ int count = 1;
+ }
+
+ /**
+ * A minimal implementation of a Bag that can store elements and a count.
+ *
+ * <p>For the intended purpose the Bag does not have to be a {@link
Collection}. It does not
+ * even have to know its own size.
+ */
+ private class TinyBag {
+ /** The backing map. */
+ private final Map<T, BagCount> map;
+
+ /**
+ * Create a new tiny bag.
+ *
+ * @param initialCapacity the initial capacity
+ */
+ TinyBag(int initialCapacity) {
+ map = new HashMap<>(initialCapacity);
+ }
+
+ /**
+ * Adds a new element to the bag, incrementing its count in the
underlying map.
+ *
+ * @param object the object to add
+ */
+ void add(T object) {
+ final BagCount mut = map.get(object);
+ if (mut == null) {
+ map.put(object, new BagCount());
+ } else {
+ mut.count++;
+ }
+ }
+
+ /**
+ * Returns the number of occurrence of the given element in this bag by
+ * looking up its count in the underlying map.
+ *
+ * @param object the object to search for
+ * @return the number of occurrences of the object, zero if not found
+ */
+ int getCount(final Object object) {
+ final BagCount count = map.get(object);
+ if (count != null) {
+ return count.count;
+ }
+ return 0;
+ }
+
+ /**
+ * Returns a possibly parallel Stream of all the entries in the bag.
+ *
+ * @return the stream
+ */
+ Stream<Map.Entry<T, BagCount>> parallelStream() {
+ return map.entrySet().parallelStream();
+ }
Review comment:
Returning a `parallelStream` might be bad here I think. Instead we should
either default to normal stream, or give the user a way to choose whether to
use a normal or a parallel stream (example [discussion about
it](https://stackoverflow.com/questions/48471554/java-parallel-stream-use-or-not-to-use)
with some good references).
I had an issue with a parallel stream in a library some months ago, and took
a while to identify where the problem was (it involved returning gridded data
from an ArcGIS server in a JAXB web service in a legacy app being ported to
Java 8... not the best of the experiences troubleshooting that).
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Issue Time Tracking
-------------------
Worklog Id: (was: 210453)
Time Spent: 2h 50m (was: 2h 40m)
> Add a generic SetSimilarity measure
> -----------------------------------
>
> Key: TEXT-155
> URL: https://issues.apache.org/jira/browse/TEXT-155
> Project: Commons Text
> Issue Type: New Feature
> Affects Versions: 1.6
> Reporter: Alex D Herbert
> Priority: Minor
> Time Spent: 2h 50m
> Remaining Estimate: 0h
>
> The {{SimilarityScore<T>}} interface can be used to compute a generic result.
> I propose to add a class that can compute the intersection between two sets
> formed from the characters. The sets must be formed from the {{CharSequence}}
> input to the {{apply}} method using a {{Function<CharSequence, Set<T>>}} to
> convert the {{CharSequence}}. This function can be passed to the
> {{SimilarityScore<T>}} during construction.
> The result can then be computed to have the size of each set and the
> intersection.
> I have created an implementation that can compute the equivalent of the
> {{JaccardSimilary}} class by creating {{Set<Character>}} and also the
> F1-score using bigrams (pairs of characters) by creating {{Set<String>}}.
> This relates to
> [Text-126|https://issues.apache.org/jira/projects/TEXT/issues/TEXT-126] which
> suggested an algorithm for the Sorensen-Dice similarity, also known as the
> F1-score.
> Here is an example:
> {code:java}
> // Match the functionality of the JaccardSimilarity class
> Function<CharSequence, Set<Character>> converter = (cs) -> {
> final Set<Character> set = new HashSet<>();
> for (int i = 0; i < cs.length(); i++) {
> set.add(cs.charAt(i));
> }
> return set;
> };
> IntersectionSimilarity<Character> similarity = new
> IntersectionSimilarity<>(converter);
> IntersectionResult result = similarity.apply("something", "something else");
> {code}
> The result has the size of set A, set B and the intersection between them.
> This class was inspired by my look through the various similarity
> implementations. All of them except the {{CosineSimilarity}} perform single
> character matching between the input {{CharSequence}}s. The
> {{CosineSimilarity}} tokenises using whitespace to create words.
> This more generic type of implementation will allow a user to determine how
> to divide the {{CharSequence}} but to create the sets that are compared, e.g.
> single characters, words, bigrams, etc.
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