/**
* 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.recommender;
import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.model.PreferenceArray;
import org.apache.mahout.cf.taste.recommender.CandidateItemsStrategy;
import org.apache.mahout.cf.taste.recommender.MostSimilarItemsCandidateItemsStrategy;
import org.apache.mahout.cf.taste.similarity.ItemSimilarity;
/**
* A variant on {@link GenericItemBasedRecommender} which is appropriate for use when no notion of preference
* value exists in the data.
*
* @see org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefUserBasedRecommender
*/
public final class GenericBooleanPrefItemBasedRecommender extends GenericItemBasedRecommender {
public GenericBooleanPrefItemBasedRecommender(DataModel dataModel, ItemSimilarity similarity) {
super(dataModel, similarity);
}
public GenericBooleanPrefItemBasedRecommender(DataModel dataModel, ItemSimilarity similarity,
CandidateItemsStrategy candidateItemsStrategy, MostSimilarItemsCandidateItemsStrategy
mostSimilarItemsCandidateItemsStrategy) {
super(dataModel, similarity, candidateItemsStrategy, mostSimilarItemsCandidateItemsStrategy);
}
/**
* This computation is in a technical sense, wrong, since in the domain of "boolean preference users" where
* all preference values are 1, this method should only ever return 1.0 or NaN. This isn't terribly useful
* however since it means results can't be ranked by preference value (all are 1). So instead this returns a
* sum of similarities.
*/
@Override
protected float doEstimatePreference(long userID, PreferenceArray preferencesFromUser, long itemID)
throws TasteException {
double[] similarities = getSimilarity().itemSimilarities(itemID, preferencesFromUser.getIDs());
boolean foundAPref = false;
double totalSimilarity = 0.0;
for (double theSimilarity : similarities) {
if (!Double.isNaN(theSimilarity)) {
foundAPref = true;
totalSimilarity += theSimilarity;
}
}
return foundAPref ? (float) totalSimilarity : Float.NaN;
}
@Override
public String toString() {
return "GenericBooleanPrefItemBasedRecommender";
}
}