/** * 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.mahout.cf.taste.impl.similarity; import org.apache.mahout.cf.taste.common.TasteException; import org.apache.mahout.cf.taste.common.Weighting; import org.apache.mahout.cf.taste.model.DataModel; import com.google.common.base.Preconditions; /** * <p> * An implementation of the cosine similarity. The result is the cosine of the angle formed between * the two preference vectors. * </p> * * <p> * Note that this similarity does not "center" its data, shifts the user's preference values so that each of their * means is 0. For this behavior, use {@link PearsonCorrelationSimilarity}, which actually is mathematically * equivalent for centered data. * </p> */ public final class UncenteredCosineSimilarity extends AbstractSimilarity { /** * @throws IllegalArgumentException if {@link DataModel} does not have preference values */ public UncenteredCosineSimilarity(DataModel dataModel) throws TasteException { this(dataModel, Weighting.UNWEIGHTED); } /** * @throws IllegalArgumentException if {@link DataModel} does not have preference values */ public UncenteredCosineSimilarity(DataModel dataModel, Weighting weighting) throws TasteException { super(dataModel, weighting, false); Preconditions.checkArgument(dataModel.hasPreferenceValues(), "DataModel doesn't have preference values"); } @Override double computeResult(int n, double sumXY, double sumX2, double sumY2, double sumXYdiff2) { if (n == 0) { return Double.NaN; } double denominator = Math.sqrt(sumX2) * Math.sqrt(sumY2); if (denominator == 0.0) { // One or both parties has -all- the same ratings; // can't really say much similarity under this measure return Double.NaN; } return sumXY / denominator; } }