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/*
 * #%L
 * Simmetrics Core
 * %%
 * Copyright (C) 2014 - 2016 Simmetrics Authors
 * %%
 * Licensed 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.
 * #L%
 */

package org.simmetrics.metrics;

import static org.simmetrics.metrics.Math.intersection;

import org.simmetrics.MultisetDistance;
import org.simmetrics.MultisetMetric;

import com.google.common.collect.Multiset;

/**
 * Calculates the Dice similarity coefficient and distance over two multisets.
 * Also known as quantitative version of the Dice similarity coefficient. The
 * similarity is defined as twice the shared information (intersection) divided
 * by the sum of cardinalities.
 * 

* * similarity(a,b) = 2 * ∣a ∩ b∣ / (∣a∣ + ∣b∣) *
* distance(a,b) = 1 - similarity(a,b) *
*

* * Implementation based on the ideas as outlined in How to Strike a * Match by Simon White. To create the described metric use: *

*

{@code
 * import static org.simmetrics.StringMetricBuilder.with;
 *  
 *  ...
 *  
 * with(new SimonWhite())
 *   .tokenize(Tokenizers.qGram(2))
 *   .build();
 * }
 * 
* *

* The Dice similarity coefficient is identical to Simon White, but unlike Simon * White the occurrence (cardinality) of an entry is not taken into account. * E.g. {@code [hello, world]} and {@code [hello, world, hello, world]} would be * identical when compared with Dice but are dissimilar when Simon White is * used. *

* This class is immutable and thread-safe. * * @see Dice * @see Wikipedia - Sørensen–Dice coefficient * * @param * type of the token * */ public final class SimonWhite implements MultisetMetric, MultisetDistance { @Override public float compare(Multiset a, Multiset b) { if (a.isEmpty() && b.isEmpty()) { return 1.0f; } if (a.isEmpty() || b.isEmpty()) { return 0.0f; } // 2 * ∣a ∩ b∣ / (∣a∣ + ∣b∣) return (2.0f * intersection(a, b).size()) / (a.size() + b.size()); } @Override public float distance(Multiset a, Multiset b) { return 1.0f - compare(a, b); } @Override public String toString() { return "SimonWhite"; } }





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