/*
* 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.example.bookcrossing;
import java.util.Collection;
import java.util.List;
import org.apache.mahout.cf.taste.common.Refreshable;
import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood;
import org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender;
import org.apache.mahout.cf.taste.impl.similarity.CachingUserSimilarity;
import org.apache.mahout.cf.taste.impl.similarity.EuclideanDistanceSimilarity;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;
import org.apache.mahout.cf.taste.recommender.IDRescorer;
import org.apache.mahout.cf.taste.recommender.RecommendedItem;
import org.apache.mahout.cf.taste.recommender.Recommender;
import org.apache.mahout.cf.taste.similarity.UserSimilarity;
/**
* A simple {@link Recommender} implemented for the Book Crossing demo.
* See the <a href="http://www.informatik.uni-freiburg.de/~cziegler/BX/">Book Crossing site</a>.
*/
public final class BookCrossingRecommender implements Recommender {
private final Recommender recommender;
public BookCrossingRecommender(DataModel bcModel) throws TasteException {
UserSimilarity similarity = new CachingUserSimilarity(new EuclideanDistanceSimilarity(bcModel), bcModel);
UserNeighborhood neighborhood = new NearestNUserNeighborhood(10, 0.2, similarity, bcModel, 0.2);
recommender = new GenericUserBasedRecommender(bcModel, neighborhood, similarity);
}
@Override
public List<RecommendedItem> recommend(long userID, int howMany) throws TasteException {
return recommender.recommend(userID, howMany);
}
@Override
public List<RecommendedItem> recommend(long userID, int howMany, IDRescorer rescorer) throws TasteException {
return recommender.recommend(userID, howMany, rescorer);
}
@Override
public float estimatePreference(long userID, long itemID) throws TasteException {
return recommender.estimatePreference(userID, itemID);
}
@Override
public void setPreference(long userID, long itemID, float value) throws TasteException {
recommender.setPreference(userID, itemID, value);
}
@Override
public void removePreference(long userID, long itemID) throws TasteException {
recommender.removePreference(userID, itemID);
}
@Override
public DataModel getDataModel() {
return recommender.getDataModel();
}
@Override
public void refresh(Collection<Refreshable> alreadyRefreshed) {
recommender.refresh(alreadyRefreshed);
}
@Override
public String toString() {
return "BookCrossingRecommender[recommender:" + recommender + ']';
}
}