/**
* 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.impl.common.LongPrimitiveIterator;
import org.apache.mahout.cf.taste.impl.common.SamplingLongPrimitiveIterator;
import org.apache.mahout.cf.taste.impl.recommender.TopItems;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.similarity.UserSimilarity;
import com.google.common.base.Preconditions;
/**
* <p>
* Computes a neighborhood consisting of the nearest n users to a given user. "Nearest" is defined by the
* given {@link UserSimilarity}.
* </p>
*/
public final class NearestNUserNeighborhood extends AbstractUserNeighborhood {
private final int n;
private final double minSimilarity;
/**
* @param n neighborhood size; capped at the number of users in the data model
* @throws IllegalArgumentException
* if {@code n < 1}, or userSimilarity or dataModel are {@code null}
*/
public NearestNUserNeighborhood(int n, UserSimilarity userSimilarity, DataModel dataModel) throws TasteException {
this(n, Double.NEGATIVE_INFINITY, userSimilarity, dataModel, 1.0);
}
/**
* @param n neighborhood size; capped at the number of users in the data model
* @param minSimilarity minimal similarity required for neighbors
* @throws IllegalArgumentException
* if {@code n < 1}, or userSimilarity or dataModel are {@code null}
*/
public NearestNUserNeighborhood(int n,
double minSimilarity,
UserSimilarity userSimilarity,
DataModel dataModel) throws TasteException {
this(n, minSimilarity, userSimilarity, dataModel, 1.0);
}
/**
* @param n neighborhood size; capped at the number of users in the data model
* @param minSimilarity minimal similarity required for neighbors
* @param samplingRate percentage of users to consider when building neighborhood -- decrease to trade quality for
* performance
* @throws IllegalArgumentException
* if {@code n < 1} or samplingRate is NaN or not in (0,1], or userSimilarity or dataModel are
* {@code null}
*/
public NearestNUserNeighborhood(int n,
double minSimilarity,
UserSimilarity userSimilarity,
DataModel dataModel,
double samplingRate) throws TasteException {
super(userSimilarity, dataModel, samplingRate);
Preconditions.checkArgument(n >= 1, "n must be at least 1");
int numUsers = dataModel.getNumUsers();
this.n = n > numUsers ? numUsers : n;
this.minSimilarity = minSimilarity;
}
@Override
public long[] getUserNeighborhood(long userID) throws TasteException {
DataModel dataModel = getDataModel();
UserSimilarity userSimilarityImpl = getUserSimilarity();
TopItems.Estimator<Long> estimator = new Estimator(userSimilarityImpl, userID, minSimilarity);
LongPrimitiveIterator userIDs = SamplingLongPrimitiveIterator.maybeWrapIterator(dataModel.getUserIDs(),
getSamplingRate());
return TopItems.getTopUsers(n, userIDs, null, estimator);
}
@Override
public String toString() {
return "NearestNUserNeighborhood";
}
private static final class Estimator implements TopItems.Estimator<Long> {
private final UserSimilarity userSimilarityImpl;
private final long theUserID;
private final double minSim;
private Estimator(UserSimilarity userSimilarityImpl, long theUserID, double minSim) {
this.userSimilarityImpl = userSimilarityImpl;
this.theUserID = theUserID;
this.minSim = minSim;
}
@Override
public double estimate(Long userID) throws TasteException {
if (userID == theUserID) {
return Double.NaN;
}
double sim = userSimilarityImpl.userSimilarity(theUserID, userID);
return sim >= minSim ? sim : Double.NaN;
}
}
}