Java tutorial
/** * 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 java.util.ArrayList; import java.util.Collections; import java.util.Iterator; import java.util.List; import java.util.PriorityQueue; import java.util.Queue; import com.google.common.base.Preconditions; import org.apache.mahout.cf.taste.common.NoSuchItemException; import org.apache.mahout.cf.taste.common.NoSuchUserException; import org.apache.mahout.cf.taste.common.TasteException; import org.apache.mahout.cf.taste.impl.common.LongPrimitiveIterator; import org.apache.mahout.cf.taste.impl.similarity.GenericItemSimilarity; import org.apache.mahout.cf.taste.impl.similarity.GenericUserSimilarity; import org.apache.mahout.cf.taste.recommender.IDRescorer; import org.apache.mahout.cf.taste.recommender.RecommendedItem; /** * <p> * A simple class that refactors the "find top N things" logic that is used in several places. * </p> */ public final class TopItems { private static final long[] NO_IDS = new long[0]; private TopItems() { } public static List<RecommendedItem> getTopItems(int howMany, LongPrimitiveIterator possibleItemIDs, IDRescorer rescorer, Estimator<Long> estimator) throws TasteException { Preconditions.checkArgument(possibleItemIDs != null, "possibleItemIDs is null"); Preconditions.checkArgument(estimator != null, "estimator is null"); Queue<RecommendedItem> topItems = new PriorityQueue<>(howMany + 1, Collections.reverseOrder(ByValueRecommendedItemComparator.getInstance())); boolean full = false; double lowestTopValue = Double.NEGATIVE_INFINITY; while (possibleItemIDs.hasNext()) { long itemID = possibleItemIDs.next(); if (rescorer == null || !rescorer.isFiltered(itemID)) { double preference; try { preference = estimator.estimate(itemID); } catch (NoSuchItemException nsie) { continue; } double rescoredPref = rescorer == null ? preference : rescorer.rescore(itemID, preference); if (!Double.isNaN(rescoredPref) && (!full || rescoredPref > lowestTopValue)) { topItems.add(new GenericRecommendedItem(itemID, (float) rescoredPref)); if (full) { topItems.poll(); } else if (topItems.size() > howMany) { full = true; topItems.poll(); } lowestTopValue = topItems.peek().getValue(); } } } int size = topItems.size(); if (size == 0) { return Collections.emptyList(); } List<RecommendedItem> result = new ArrayList<>(size); result.addAll(topItems); Collections.sort(result, ByValueRecommendedItemComparator.getInstance()); return result; } public static long[] getTopUsers(int howMany, LongPrimitiveIterator allUserIDs, IDRescorer rescorer, Estimator<Long> estimator) throws TasteException { Queue<SimilarUser> topUsers = new PriorityQueue<>(howMany + 1, Collections.reverseOrder()); boolean full = false; double lowestTopValue = Double.NEGATIVE_INFINITY; while (allUserIDs.hasNext()) { long userID = allUserIDs.next(); if (rescorer != null && rescorer.isFiltered(userID)) { continue; } double similarity; try { similarity = estimator.estimate(userID); } catch (NoSuchUserException nsue) { continue; } double rescoredSimilarity = rescorer == null ? similarity : rescorer.rescore(userID, similarity); if (!Double.isNaN(rescoredSimilarity) && (!full || rescoredSimilarity > lowestTopValue)) { topUsers.add(new SimilarUser(userID, rescoredSimilarity)); if (full) { topUsers.poll(); } else if (topUsers.size() > howMany) { full = true; topUsers.poll(); } lowestTopValue = topUsers.peek().getSimilarity(); } } int size = topUsers.size(); if (size == 0) { return NO_IDS; } List<SimilarUser> sorted = new ArrayList<>(size); sorted.addAll(topUsers); Collections.sort(sorted); long[] result = new long[size]; int i = 0; for (SimilarUser similarUser : sorted) { result[i++] = similarUser.getUserID(); } return result; } /** * <p> * Thanks to tsmorton for suggesting this functionality and writing part of the code. * </p> * * @see GenericItemSimilarity#GenericItemSimilarity(Iterable, int) * @see GenericItemSimilarity#GenericItemSimilarity(org.apache.mahout.cf.taste.similarity.ItemSimilarity, * org.apache.mahout.cf.taste.model.DataModel, int) */ public static List<GenericItemSimilarity.ItemItemSimilarity> getTopItemItemSimilarities(int howMany, Iterator<GenericItemSimilarity.ItemItemSimilarity> allSimilarities) { Queue<GenericItemSimilarity.ItemItemSimilarity> topSimilarities = new PriorityQueue<>(howMany + 1, Collections.reverseOrder()); boolean full = false; double lowestTopValue = Double.NEGATIVE_INFINITY; while (allSimilarities.hasNext()) { GenericItemSimilarity.ItemItemSimilarity similarity = allSimilarities.next(); double value = similarity.getValue(); if (!Double.isNaN(value) && (!full || value > lowestTopValue)) { topSimilarities.add(similarity); if (full) { topSimilarities.poll(); } else if (topSimilarities.size() > howMany) { full = true; topSimilarities.poll(); } lowestTopValue = topSimilarities.peek().getValue(); } } int size = topSimilarities.size(); if (size == 0) { return Collections.emptyList(); } List<GenericItemSimilarity.ItemItemSimilarity> result = new ArrayList<>(size); result.addAll(topSimilarities); Collections.sort(result); return result; } public static List<GenericUserSimilarity.UserUserSimilarity> getTopUserUserSimilarities(int howMany, Iterator<GenericUserSimilarity.UserUserSimilarity> allSimilarities) { Queue<GenericUserSimilarity.UserUserSimilarity> topSimilarities = new PriorityQueue<>(howMany + 1, Collections.reverseOrder()); boolean full = false; double lowestTopValue = Double.NEGATIVE_INFINITY; while (allSimilarities.hasNext()) { GenericUserSimilarity.UserUserSimilarity similarity = allSimilarities.next(); double value = similarity.getValue(); if (!Double.isNaN(value) && (!full || value > lowestTopValue)) { topSimilarities.add(similarity); if (full) { topSimilarities.poll(); } else if (topSimilarities.size() > howMany) { full = true; topSimilarities.poll(); } lowestTopValue = topSimilarities.peek().getValue(); } } int size = topSimilarities.size(); if (size == 0) { return Collections.emptyList(); } List<GenericUserSimilarity.UserUserSimilarity> result = new ArrayList<>(size); result.addAll(topSimilarities); Collections.sort(result); return result; } public interface Estimator<T> { double estimate(T thing) throws TasteException; } }