/**
* 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.neighborhood;
import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.similarity.UserSimilarity;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.model.User;
import org.apache.mahout.cf.taste.impl.recommender.TopItems;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.Collection;
import java.util.Collections;
import java.util.List;
/**
* <p>Computes a neighborhood consisting of the nearest n {@link User}s to a given {@link User}.
* "Nearest" is defined by the given {@link org.apache.mahout.cf.taste.similarity.UserSimilarity}.</p>
*/
public final class NearestNUserNeighborhood extends AbstractUserNeighborhood {
private static final Logger log = LoggerFactory.getLogger(NearestNUserNeighborhood.class);
private final int n;
private final double minSimilarity;
/**
* @param n neighborhood size
* @param userSimilarity nearness metric
* @param dataModel data model
* @throws IllegalArgumentException if n < 1, or userSimilarity or dataModel are <code>null</code>
*/
public NearestNUserNeighborhood(int n,
UserSimilarity userSimilarity,
DataModel dataModel) {
this(n, Double.NEGATIVE_INFINITY, userSimilarity, dataModel, 1.0);
}
/**
* @param n neighborhood size
* @param minSimilarity minimal similarity required for neighbors
* @param userSimilarity nearness metric
* @param dataModel data model
* @throws IllegalArgumentException if n < 1, or userSimilarity or dataModel are <code>null</code>
*/
public NearestNUserNeighborhood(int n, double minSimilarity,
UserSimilarity userSimilarity,
DataModel dataModel) {
this(n, minSimilarity, userSimilarity, dataModel, 1.0);
}
/**
* @param n neighborhood size
* @param minSimilarity minimal similarity required for neighbors
* @param userSimilarity nearness metric
* @param dataModel data model
* @param samplingRate percentage of users to consider when building neighborhood -- decrease to
* trade quality for performance
* @throws IllegalArgumentException if n < 1 or samplingRate is NaN or not in (0,1],
* or userSimilarity or dataModel are <code>null</code>
*/
public NearestNUserNeighborhood(int n, double minSimilarity,
UserSimilarity userSimilarity,
DataModel dataModel,
double samplingRate) {
super(userSimilarity, dataModel, samplingRate);
if (n < 1) {
throw new IllegalArgumentException("n must be at least 1");
}
this.n = n;
this.minSimilarity = minSimilarity;
}
@Override
public Collection<User> getUserNeighborhood(Object userID) throws TasteException {
log.trace("Computing neighborhood around user ID '{}'", userID);
DataModel dataModel = getDataModel();
User theUser = dataModel.getUser(userID);
UserSimilarity userSimilarityImpl = getUserSimilarity();
TopItems.Estimator<User> estimator = new Estimator(userSimilarityImpl, theUser, minSimilarity);
List<User> neighborhood = TopItems.getTopUsers(n, dataModel.getUsers(), null, estimator);
log.trace("UserNeighborhood around user ID '{}' is: {}", userID, neighborhood);
return Collections.unmodifiableList(neighborhood);
}
@Override
public String toString() {
return "NearestNUserNeighborhood";
}
private static class Estimator implements TopItems.Estimator<User> {
private final UserSimilarity userSimilarityImpl;
private final User theUser;
private final double minSim;
private Estimator(UserSimilarity userSimilarityImpl, User theUser, double minSim) {
this.userSimilarityImpl = userSimilarityImpl;
this.theUser = theUser;
this.minSim = minSim;
}
@Override
public double estimate(User user) throws TasteException {
if (user.equals(theUser)) {
return Double.NaN;
}
double sim = userSimilarityImpl.userSimilarity(theUser, user);
return (sim >= minSim) ? sim : Double.NaN;
}
}
}