1 | package de.ugoe.cs.eventbench.models;
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2 |
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3 | import java.util.LinkedList;
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4 | import java.util.List;
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5 | import java.util.Random;
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6 |
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7 | import de.ugoe.cs.eventbench.data.Event;
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8 |
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9 | /**
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10 | * <p>Implements high-order Markov models.</p>
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11 | *
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12 | * @author Steffen Herbold
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13 | * @version 1.0
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14 | */
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15 | public class HighOrderMarkovModel extends TrieBasedModel {
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16 |
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17 | /**
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18 | * <p>
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19 | * Id for object serialization.
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20 | * </p>
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21 | */
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22 | private static final long serialVersionUID = 1L;
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23 |
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24 | /**
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25 | * <p>Constructor. Creates a new HighOrderMarkovModel with a defined Markov order.</p>
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26 | * @param maxOrder Markov order of the model
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27 | * @param r random number generator used by probabilistic methods of the class
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28 | */
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29 | public HighOrderMarkovModel(int maxOrder, Random r) {
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30 | super(maxOrder, r);
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31 | }
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32 |
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33 | /**
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34 | * <p>
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35 | * Calculates the probability of the next Event being symbol based on the order of the Markov model. The order is defined in the constructor {@link #HighOrderMarkovModel(int, Random)}.
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36 | * </p>
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37 | * @see de.ugoe.cs.eventbench.models.IStochasticProcess#getProbability(java.util.List, de.ugoe.cs.eventbench.data.Event)
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38 | */
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39 | @Override
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40 | public double getProbability(List<? extends Event<?>> context, Event<?> symbol) {
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41 | double result = 0.0d;
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42 |
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43 | List<Event<?>> contextCopy;
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44 | if( context.size()>=trieOrder ) {
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45 | contextCopy = new LinkedList<Event<?>>(context.subList(context.size()-trieOrder+1, context.size()));
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46 | } else {
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47 | contextCopy = new LinkedList<Event<?>>(context);
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48 | }
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49 |
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50 |
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51 | List<Event<?>> followers = trie.getFollowingSymbols(contextCopy);
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52 | int sumCountFollowers = 0; // N(s\sigma')
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53 | for( Event<?> follower : followers ) {
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54 | sumCountFollowers += trie.getCount(contextCopy, follower);
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55 | }
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56 |
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57 | int countSymbol = trie.getCount(contextCopy, symbol);
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58 | if( sumCountFollowers!=0 ) {
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59 | result = ((double) countSymbol / sumCountFollowers);
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60 | }
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61 |
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62 | return result;
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63 | }
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64 |
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65 | }
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