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/*
 * SimMetrics - SimMetrics is a java library of Similarity or Distance Metrics,
 * e.g. Levenshtein Distance, that provide float based similarity measures
 * between String Data. All metrics return consistent measures rather than
 * unbounded similarity scores.
 * 
 * Copyright (C) 2014 SimMetrics authors
 * 
 * This file is part of SimMetrics. This program is free software: you can
 * redistribute it and/or modify it under the terms of the GNU General Public
 * License as published by the Free Software Foundation, either version 3 of the
 * License, or (at your option) any later version.
 * 
 * This program is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 * FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
 * details.
 * 
 * You should have received a copy of the GNU General Public License along with
 * SimMetrics. If not, see .
 */
package org.simmetrics.metrics;

import java.util.HashSet;
import java.util.Set;

import org.simmetrics.SetMetric;

import static java.lang.Math.sqrt;

/**
 * Cosine Similarity algorithm providing a similarity measure between two set
 * from the angular divergence within token based vector space.
 * 

* This class is immutable and thread-safe. * * @see Wikipedia * Cosine similarity * @param * type of the token */ public class CosineSimilarity implements SetMetric { @Override public float compare(Set a, Set b) { if (a.isEmpty() && b.isEmpty()) { return 1.0f; } if (a.isEmpty() || b.isEmpty()) { return 0.0f; } final Set all = new HashSet<>(); all.addAll(a); all.addAll(b); // Implementation note: Dot product of two binary vectors is the // intersection of two sets final int commonTerms = (a.size() + b.size()) - all.size(); // Implementation note: Magnitude of a binary vectors is sqrt of its // size. return (float) (commonTerms / (sqrt(a.size()) * sqrt(b.size()))); } @Override public String toString() { return "CosineSimilarity"; } }