[927] | 1 | // Copyright 2012 Georg-August-Universität Göttingen, Germany
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| 2 | //
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| 3 | // Licensed under the Apache License, Version 2.0 (the "License");
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| 4 | // you may not use this file except in compliance with the License.
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| 5 | // You may obtain a copy of the License at
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| 6 | //
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| 7 | // http://www.apache.org/licenses/LICENSE-2.0
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| 8 | //
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| 9 | // Unless required by applicable law or agreed to in writing, software
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| 10 | // distributed under the License is distributed on an "AS IS" BASIS,
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| 11 | // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 12 | // See the License for the specific language governing permissions and
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| 13 | // limitations under the License.
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| 14 |
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[922] | 15 | package de.ugoe.cs.autoquest.usageprofiles;
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[518] | 16 |
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| 17 | import java.util.LinkedList;
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| 18 | import java.util.List;
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| 19 | import java.util.Random;
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| 20 |
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[922] | 21 | import de.ugoe.cs.autoquest.eventcore.Event;
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| 22 | import de.ugoe.cs.autoquest.eventcore.StringEventType;
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[518] | 23 |
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| 24 | /**
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| 25 | * <p>
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[559] | 26 | * This class provides functions to create flattened first-order Markov models from
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| 27 | * {@link HighOrderMarkovModel}s and {@link PredictionByPartialMatch} models through state
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| 28 | * splitting.
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[518] | 29 | * </p>
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| 30 | * <p>
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[559] | 31 | * If possible, the normal high-order markov model should be used, as the Events may be broken by
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| 32 | * the flattener, as, e.g., the information {@link ReplayableEvent}s contain is not preserved.
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[518] | 33 | * </p>
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| 34 | *
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| 35 | * @author Steffen Herbold
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| 36 | * @version 1.0
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| 37 | */
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| 38 | public class ModelFlattener {
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| 39 |
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[559] | 40 | private static final String EVENT_SEPARATOR = "-=-";
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[518] | 41 |
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[559] | 42 | Trie<Event> firstOrderTrie;
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[518] | 43 |
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[559] | 44 | /**
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| 45 | * <p>
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| 46 | * Takes a {@link HighOrderMarkovModel} and returns a {@link FirstOrderMarkovModel} that
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| 47 | * conserves the high-order memory through state splitting.
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| 48 | * </p>
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| 49 | *
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| 50 | * @param model
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| 51 | * model that is flattened
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| 52 | * @return flattened first-order Markov model
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| 53 | */
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| 54 | public FirstOrderMarkovModel flattenHighOrderMarkovModel(HighOrderMarkovModel model) {
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| 55 | int markovOrder = model.trieOrder - 1;
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| 56 | FirstOrderMarkovModel firstOrderModel = new FirstOrderMarkovModel(new Random());
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| 57 | firstOrderModel.trieOrder = 2;
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| 58 | if (markovOrder == 1) {
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| 59 | firstOrderModel.trie = new Trie<Event>(model.trie);
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| 60 | firstOrderModel.trieOrder = 2;
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| 61 | }
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| 62 | else {
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| 63 | firstOrderTrie = new Trie<Event>();
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| 64 | TrieNode<Event> rootNode = model.trie.find(null);
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| 65 | generateFirstOrderTrie(rootNode, new LinkedList<String>(), markovOrder);
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| 66 | firstOrderTrie.updateKnownSymbols();
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| 67 | firstOrderModel.trie = firstOrderTrie;
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| 68 | }
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[518] | 69 |
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[559] | 70 | return firstOrderModel;
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| 71 | }
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[518] | 72 |
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[559] | 73 | /**
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| 74 | * <p>
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| 75 | * <b>This method is not available yet and always return null!</b>
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| 76 | * </p>
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| 77 | * <p>
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| 78 | * Takes a {@link PredictionByPartialMatch} model and returns a {@link FirstOrderMarkovModel}
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| 79 | * that conserves the high-order memory through state splitting.
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| 80 | * </p>
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| 81 | *
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| 82 | * @param model
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| 83 | * model that is flattened
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| 84 | * @return flattened first-order Markov model
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| 85 | */
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| 86 | public FirstOrderMarkovModel flattenPredictionByPartialMatch(PredictionByPartialMatch model) {
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| 87 | // TODO implement method
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| 88 | return null;
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| 89 | }
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[518] | 90 |
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[559] | 91 | /**
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| 92 | * <p>
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| 93 | * Converts all nodes of the given depth into first-order node through state-splitting. For each
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| 94 | * node at the given depth a new node is created and appropriate transitions will be added.
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| 95 | * </p>
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| 96 | * <p>
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| 97 | * This method traverses through the tree recursively. If the recursion reaches the desired
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| 98 | * depth in the tree, node are added.
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| 99 | * </p>
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| 100 | *
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| 101 | * @param currentNode
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| 102 | * node whose sub-trie is currently traversed
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| 103 | * @param parentIDs
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| 104 | * ID strings of the ancestors of the currentNode
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| 105 | * @param depth
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| 106 | * depth to go - NOT the current depth.
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| 107 | */
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| 108 | private void generateFirstOrderTrie(TrieNode<Event> currentNode,
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| 109 | List<String> parentIDs,
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| 110 | int depth)
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| 111 | {
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| 112 | for (TrieNode<Event> child : currentNode.getChildren()) {
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| 113 | String currentId = child.getSymbol().getId();
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| 114 | if (depth > 1) {
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| 115 | List<String> childParentIDs = new LinkedList<String>(parentIDs);
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| 116 | childParentIDs.add(currentId);
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| 117 | generateFirstOrderTrie(child, childParentIDs, depth - 1);
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[518] | 118 |
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[559] | 119 | }
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| 120 | else {
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| 121 | StringBuilder firstOrderID = new StringBuilder();
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| 122 | for (String parentID : parentIDs) {
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| 123 | firstOrderID.append(parentID + EVENT_SEPARATOR);
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| 124 | }
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| 125 | firstOrderID.append(currentId);
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| 126 | TrieNode<Event> firstOrderNode =
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| 127 | firstOrderTrie.getChildCreate(new Event(new StringEventType(firstOrderID
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| 128 | .toString())));
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| 129 | firstOrderNode.setCount(child.getCount());
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| 130 | for (TrieNode<Event> transitionChild : child.getChildren()) {
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| 131 | StringBuilder transitionID = new StringBuilder();
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| 132 | for (String parentID : parentIDs.subList(1, parentIDs.size())) {
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| 133 | transitionID.append(parentID + EVENT_SEPARATOR);
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| 134 | }
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| 135 | transitionID.append(currentId + EVENT_SEPARATOR);
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| 136 | transitionID.append(transitionChild.getSymbol().getId());
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| 137 | TrieNode<Event> firstOrderTransitionChild =
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| 138 | firstOrderNode.getChildCreate(new Event(new StringEventType(transitionID
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| 139 | .toString())));
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| 140 | firstOrderTransitionChild.setCount(transitionChild.getCount());
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| 141 | }
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| 142 | }
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| 143 | }
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| 144 | }
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[518] | 145 | }
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