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[DL-Learner SVN] SF.net SVN: dl-learner:[2334] trunk
|
From: <jen...@us...> - 2010-09-24 09:26:11
|
Revision: 2334
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=2334&view=rev
Author: jenslehmann
Date: 2010-09-24 09:26:02 +0000 (Fri, 24 Sep 2010)
Log Message:
-----------
renamed refinement2 to OCEL (OWL Class Expression Learner)
Modified Paths:
--------------
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ExampleBasedHeuristic.java
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ExampleBasedNode.java
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/FlexibleHeuristic.java
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/LexicographicHeuristic.java
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/MultiHeuristic.java
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/NodeComparatorStable.java
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ROLearner2.java
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/SubsumptionComparator.java
trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java
trunk/components-core/src/main/java/org/dllearner/core/configurators/ComponentFactory.java
trunk/components-core/src/main/java/org/dllearner/core/configurators/ROLComponent2Configurator.java
trunk/components-core/src/main/java/org/dllearner/examples/KRKModular.java
trunk/components-core/src/main/java/org/dllearner/utilities/JamonMonitorLogger.java
trunk/components-core/src/main/java/org/dllearner/utilities/components/ComponentCombo.java
trunk/components-core/src/main/java/org/dllearner/utilities/examples/ExampleDataCollector.java
trunk/components-core/src/test/java/org/dllearner/test/ComponentTest.java
trunk/components-core/src/test/java/org/dllearner/test/SworeTest.java
trunk/components-core/src/test/java/org/dllearner/test/junit/RefinementOperatorTests.java
trunk/interfaces/src/main/java/org/dllearner/cli/ConfMapper.java
trunk/interfaces/src/main/java/org/dllearner/cli/Start.java
trunk/interfaces/src/main/java/org/dllearner/gui/EBNodeTreeModel.java
trunk/interfaces/src/main/java/org/dllearner/gui/RunPanel.java
trunk/interfaces/src/main/java/org/dllearner/gui/SearchTree.java
trunk/interfaces/src/main/java/org/dllearner/gui/StartGUI.java
trunk/interfaces/src/main/java/org/dllearner/gui/TreeWindow.java
trunk/scripts/src/main/java/org/dllearner/examples/KRKModular.java
trunk/scripts/src/main/java/org/dllearner/scripts/DumbLPFinder.java
trunk/scripts/src/main/java/org/dllearner/scripts/NewSample.java
trunk/scripts/src/main/java/org/dllearner/scripts/Sample.java
trunk/scripts/src/main/java/org/dllearner/scripts/SemanticBible.java
trunk/scripts/src/main/java/org/dllearner/scripts/SemanticBibleComparison.java
trunk/scripts/src/main/java/org/dllearner/scripts/WikipediaCategoryCleaner.java
trunk/scripts/src/main/java/org/dllearner/scripts/tiger/TestIterativeLearning.java
trunk/scripts/src/main/java/org/dllearner/scripts/tiger/TestQueries.java
Added Paths:
-----------
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/OCEL.java
Removed Paths:
-------------
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ROLComponent2.java
trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/
Property Changed:
----------------
trunk/interfaces/
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ExampleBasedHeuristic.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/ExampleBasedHeuristic.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ExampleBasedHeuristic.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -17,7 +17,7 @@
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
*/
-package org.dllearner.algorithms.refinement2;
+package org.dllearner.algorithms.ocel;
import java.util.Comparator;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ExampleBasedNode.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/ExampleBasedNode.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ExampleBasedNode.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -18,7 +18,7 @@
*
*/
-package org.dllearner.algorithms.refinement2;
+package org.dllearner.algorithms.ocel;
import java.text.DecimalFormat;
import java.util.Map;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/FlexibleHeuristic.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/FlexibleHeuristic.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/FlexibleHeuristic.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -18,7 +18,7 @@
*
*/
-package org.dllearner.algorithms.refinement2;
+package org.dllearner.algorithms.ocel;
import org.dllearner.utilities.owl.ConceptComparator;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/LexicographicHeuristic.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/LexicographicHeuristic.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/LexicographicHeuristic.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -18,7 +18,7 @@
*
*/
-package org.dllearner.algorithms.refinement2;
+package org.dllearner.algorithms.ocel;
import org.dllearner.utilities.owl.ConceptComparator;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/MultiHeuristic.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/MultiHeuristic.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/MultiHeuristic.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -17,7 +17,7 @@
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
*/
-package org.dllearner.algorithms.refinement2;
+package org.dllearner.algorithms.ocel;
import java.util.List;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/NodeComparatorStable.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/NodeComparatorStable.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/NodeComparatorStable.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -18,7 +18,7 @@
*
*/
-package org.dllearner.algorithms.refinement2;
+package org.dllearner.algorithms.ocel;
import java.util.Comparator;
Copied: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/OCEL.java (from rev 2333, trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/ROLComponent2.java)
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/OCEL.java (rev 0)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/OCEL.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -0,0 +1,503 @@
+/**
+ * Copyright (C) 2007-2008, Jens Lehmann
+ *
+ * This file is part of DL-Learner.
+ *
+ * DL-Learner is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * DL-Learner is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program. If not, see <http://www.gnu.org/licenses/>.
+ *
+ */
+
+package org.dllearner.algorithms.ocel;
+
+import java.io.File;
+import java.util.Collection;
+import java.util.LinkedList;
+import java.util.List;
+import java.util.Set;
+import java.util.TreeSet;
+
+import org.apache.log4j.Level;
+import org.apache.log4j.Logger;
+import org.dllearner.core.ComponentInitException;
+import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.LearningProblem;
+import org.dllearner.core.ReasonerComponent;
+import org.dllearner.core.configurators.ROLComponent2Configurator;
+import org.dllearner.core.options.BooleanConfigOption;
+import org.dllearner.core.options.CommonConfigMappings;
+import org.dllearner.core.options.CommonConfigOptions;
+import org.dllearner.core.options.ConfigEntry;
+import org.dllearner.core.options.ConfigOption;
+import org.dllearner.core.options.DoubleConfigOption;
+import org.dllearner.core.options.IntegerConfigOption;
+import org.dllearner.core.options.InvalidConfigOptionValueException;
+import org.dllearner.core.options.StringConfigOption;
+import org.dllearner.core.owl.ClassHierarchy;
+import org.dllearner.core.owl.Description;
+import org.dllearner.core.owl.NamedClass;
+import org.dllearner.core.owl.ObjectProperty;
+import org.dllearner.learningproblems.EvaluatedDescriptionPosNeg;
+import org.dllearner.learningproblems.PosNegLP;
+import org.dllearner.learningproblems.PosOnlyLP;
+import org.dllearner.learningproblems.ScorePosNeg;
+import org.dllearner.reasoning.ReasonerType;
+import org.dllearner.refinementoperators.RhoDRDown;
+import org.dllearner.utilities.Files;
+import org.dllearner.utilities.Helper;
+
+/**
+ * The DL-Learner learning algorithm component for the example
+ * based refinement operator approach. It handles all
+ * configuration options, creates the corresponding objects and
+ * passes them to the actual refinement operator, heuristic, and
+ * learning algorithm implementations.
+ *
+ * Note: The options supported by the ROLearner component and this
+ * one are not equal. Options that have been dropped for now:
+ * - horizontal expansion factor: The goal of the algorithm will
+ * be to (hopefully) be able to learn long and complex concepts
+ * more efficiently.
+ * A horizontal expansion factor has its benefits, but limits
+ * the length of concepts learnable in reasonable time to
+ * about 15 with its default value of 0.6 and a small sized
+ * background knowledge base. We hope to get more fine-grained
+ * control of whether it makes sense to extend a node with
+ * more sophisticated heuristics.
+ * Dropping the horizontal expansion factor means that the
+ * completeness of the algorithm depends on the heuristic.
+ *
+ * @author Jens Lehmann
+ *
+ */
+public class OCEL extends LearningAlgorithm {
+
+ private ROLComponent2Configurator configurator;
+ @Override
+ public ROLComponent2Configurator getConfigurator(){
+ return configurator;
+ }
+
+ // actual algorithm
+ private ROLearner2 algorithm;
+ private static Logger logger = Logger
+ .getLogger(OCEL.class);
+ private String logLevel = CommonConfigOptions.logLevelDefault;
+ RhoDRDown operator;
+
+ // configuration options
+ private boolean writeSearchTree;
+ private File searchTreeFile;
+ private boolean replaceSearchTree = false;
+ private static String defaultSearchTreeFile = "log/searchTree.txt";
+ private String heuristic = "multi";
+ Set<NamedClass> allowedConcepts;
+ Set<ObjectProperty> allowedRoles;
+ Set<NamedClass> ignoredConcepts;
+ Set<ObjectProperty> ignoredRoles;
+ // these are computed as the result of the previous four settings
+ Set<NamedClass> usedConcepts;
+ Set<ObjectProperty> usedRoles;
+ private boolean applyAllFilter = true;
+ private boolean applyExistsFilter = true;
+ private boolean useTooWeakList = true;
+ private boolean useOverlyGeneralList = true;
+ private boolean useShortConceptConstruction = true;
+ private boolean improveSubsumptionHierarchy = true;
+ private boolean useAllConstructor = CommonConfigOptions.useAllConstructorDefault;
+ private boolean useExistsConstructor = CommonConfigOptions.useExistsConstructorDefault;
+ private boolean useHasValueConstructor = CommonConfigOptions.useHasValueConstructorDefault;
+ private int valueFrequencyThreshold = CommonConfigOptions.valueFrequencyThresholdDefault;
+ private boolean useCardinalityRestrictions = CommonConfigOptions.useCardinalityRestrictionsDefault;
+ private boolean useNegation = CommonConfigOptions.useNegationDefault;
+ private boolean useBooleanDatatypes = CommonConfigOptions.useBooleanDatatypesDefault;
+ private boolean useDoubleDatatypes = CommonConfigOptions.useDoubleDatatypesDefault;
+ private static double noisePercentageDefault = 0.0;
+ private double noisePercentage = noisePercentageDefault;
+ private NamedClass startClass = null;
+ //refactor this
+ private static boolean usePropernessChecksDefault = false;
+ private boolean usePropernessChecks = usePropernessChecksDefault;
+ // refactor this
+ private static int maxPosOnlyExpansionDefault = 4;
+ private int maxPosOnlyExpansion = maxPosOnlyExpansionDefault;
+ private boolean forceRefinementLengthIncrease = true;
+ //extended Options
+ //in seconds
+ private int maxExecutionTimeInSeconds = CommonConfigOptions.maxExecutionTimeInSecondsDefault;
+ private int minExecutionTimeInSeconds = CommonConfigOptions.minExecutionTimeInSecondsDefault;
+ private int guaranteeXgoodDescriptions = CommonConfigOptions.guaranteeXgoodDescriptionsDefault;
+ private int maxClassDescriptionTests = CommonConfigOptions.maxClassDescriptionTestsDefault;
+
+ // Variablen zur Einstellung der Protokollierung
+ // boolean quiet = false;
+ boolean showBenchmarkInformation = false;
+ // boolean createTreeString = false;
+ // String searchTree = new String();
+
+ // Konfiguration des Algorithmus
+ // Faktor für horizontale Erweiterung (notwendig für completeness)
+ // double horizontalExpansionFactor = 0.6;
+
+ // soll später einen Operator und eine Heuristik entgegennehmen
+ // public ROLearner(LearningProblem learningProblem, LearningProblem learningProblem2) {
+ public OCEL(PosNegLP learningProblem, ReasonerComponent reasoningService) {
+ super(learningProblem, reasoningService);
+ this.configurator = new ROLComponent2Configurator(this);
+ }
+
+ public OCEL(PosOnlyLP learningProblem, ReasonerComponent reasoningService) {
+ super(learningProblem, reasoningService);
+ this.configurator = new ROLComponent2Configurator(this);
+ }
+
+ public static Collection<Class<? extends LearningProblem>> supportedLearningProblems() {
+ Collection<Class<? extends LearningProblem>> problems = new LinkedList<Class<? extends LearningProblem>>();
+ problems.add(PosNegLP.class);
+ problems.add(PosOnlyLP.class);
+ return problems;
+ }
+
+ public static Collection<ConfigOption<?>> createConfigOptions() {
+ Collection<ConfigOption<?>> options = new LinkedList<ConfigOption<?>>();
+ options.add(new BooleanConfigOption("writeSearchTree", "specifies whether to write a search tree", false));
+ options.add(new StringConfigOption("searchTreeFile","file to use for the search tree", defaultSearchTreeFile));
+ options.add(new BooleanConfigOption("replaceSearchTree","specifies whether to replace the search tree in the log file after each run or append the new search tree", false));
+ StringConfigOption heuristicOption = new StringConfigOption("heuristic", "specifiy the heuristic to use", "lexicographic");
+ heuristicOption.setAllowedValues(new String[] {"lexicographic", "flexible"});
+ options.add(heuristicOption);
+ options.add(new BooleanConfigOption("applyAllFilter", "usage of equivalence ALL R.C AND ALL R.D = ALL R.(C AND D)", true));
+ options.add(new BooleanConfigOption("applyExistsFilter", "usage of equivalence EXISTS R.C OR EXISTS R.D = EXISTS R.(C OR D)", true));
+ options.add(new BooleanConfigOption("useTooWeakList", "try to filter out too weak concepts without sending them to the reasoner", true));
+ options.add(new BooleanConfigOption("useOverlyGeneralList", "try to find overly general concept without sending them to the reasoner", true));
+ options.add(new BooleanConfigOption("useShortConceptConstruction", "shorten concept to see whether they already exist", true));
+ DoubleConfigOption horizExp = new DoubleConfigOption("horizontalExpansionFactor", "horizontal expansion factor (see publication for description)", 0.6);
+ horizExp.setLowerLimit(0.0);
+ horizExp.setUpperLimit(1.0);
+ options.add(horizExp);
+ options.add(new BooleanConfigOption("improveSubsumptionHierarchy", "simplify subsumption hierarchy to reduce search space (see publication for description)", true));
+ options.add(CommonConfigOptions.allowedConcepts());
+ options.add(CommonConfigOptions.ignoredConcepts());
+ // allowed/ignored roles are an unstable/untested feature
+ options.add(CommonConfigOptions.allowedRoles());
+ options.add(CommonConfigOptions.ignoredRoles());
+ options.add(CommonConfigOptions.useAllConstructor());
+ options.add(CommonConfigOptions.useExistsConstructor());
+ options.add(CommonConfigOptions.useHasValueConstructor());
+ options.add(CommonConfigOptions.useDataHasValueConstructor());
+ options.add(CommonConfigOptions.valueFreqencyThreshold());
+ options.add(CommonConfigOptions.useCardinalityRestrictions());
+ options.add(CommonConfigOptions.cardinalityLimit());
+ options.add(CommonConfigOptions.useNegation());
+ options.add(CommonConfigOptions.useBooleanDatatypes());
+ options.add(CommonConfigOptions.useDoubleDatatypes());
+ options.add(CommonConfigOptions.useStringDatatypes());
+ options.add(CommonConfigOptions.maxExecutionTimeInSeconds());
+ options.add(CommonConfigOptions.minExecutionTimeInSeconds());
+ options.add(CommonConfigOptions.guaranteeXgoodDescriptions());
+ options.add(CommonConfigOptions.maxClassDescriptionTests());
+ options.add(CommonConfigOptions.getLogLevel());
+ options.add(new BooleanConfigOption("usePropernessChecks", "specifies whether to check for equivalence (i.e. discard equivalent refinements)",usePropernessChecksDefault));
+ options.add(CommonConfigOptions.getNoisePercentage());
+ options.add(CommonConfigOptions.getTerminateOnNoiseReached());
+ options.add(new StringConfigOption("startClass", "the named class which should be used to start the algorithm (GUI: needs a widget for selecting a class)"));
+ options.add(new BooleanConfigOption("forceRefinementLengthIncrease", "specifies whether nodes should be expanded until only longer refinements are reached"));
+ options.add(new DoubleConfigOption("negativeWeight", "Used to penalise errors on negative examples different from those of positive examples (lower = less importance for negatives).",1.0));
+ options.add(new DoubleConfigOption("startNodeBonus", "You can use this to give a heuristic bonus on the start node (= initially broader exploration of search space).",0.0));
+ options.add(new IntegerConfigOption("negationPenalty", "Penalty on negations (TODO: better explanation).", 0));
+ options.add(CommonConfigOptions.getExpansionPenaltyFactor(0.02));
+ options.add(CommonConfigOptions.getInstanceBasedDisjoints());
+ return options;
+ }
+
+ /* (non-Javadoc)
+ * @see org.dllearner.core.Component#applyConfigEntry(org.dllearner.core.ConfigEntry)
+ */
+ @Override
+ @SuppressWarnings({"unchecked"})
+ public <T> void applyConfigEntry(ConfigEntry<T> entry) throws InvalidConfigOptionValueException {
+ String name = entry.getOptionName();
+ if(name.equals("writeSearchTree"))
+ writeSearchTree = (Boolean) entry.getValue();
+ else if(name.equals("searchTreeFile"))
+ searchTreeFile = new File((String)entry.getValue());
+ else if(name.equals("replaceSearchTree"))
+ replaceSearchTree = (Boolean) entry.getValue();
+ else if(name.equals("heuristic")) {
+ String value = (String) entry.getValue();
+ if(value.equals("lexicographic"))
+ heuristic = "lexicographic";
+ else
+ heuristic = "flexible";
+ } else if(name.equals("allowedConcepts")) {
+ allowedConcepts = CommonConfigMappings.getAtomicConceptSet((Set<String>)entry.getValue());
+ } else if(name.equals("allowedRoles")) {
+ allowedRoles = CommonConfigMappings.getAtomicRoleSet((Set<String>)entry.getValue());
+ } else if(name.equals("ignoredConcepts")) {
+ ignoredConcepts = CommonConfigMappings.getAtomicConceptSet((Set<String>)entry.getValue());
+ } else if(name.equals("ignoredRoles")) {
+ ignoredRoles = CommonConfigMappings.getAtomicRoleSet((Set<String>)entry.getValue());
+ } else if(name.equals("applyAllFilter")) {
+ applyAllFilter = (Boolean) entry.getValue();
+ } else if(name.equals("applyExistsFilter")) {
+ applyExistsFilter = (Boolean) entry.getValue();
+ } else if(name.equals("useTooWeakList")) {
+ useTooWeakList = (Boolean) entry.getValue();
+ } else if(name.equals("useOverlyGeneralList")) {
+ useOverlyGeneralList = (Boolean) entry.getValue();
+ } else if(name.equals("useShortConceptConstruction")) {
+ useShortConceptConstruction = (Boolean) entry.getValue();
+ } else if(name.equals("improveSubsumptionHierarchy")) {
+ improveSubsumptionHierarchy = (Boolean) entry.getValue();
+ } else if(name.equals("useAllConstructor")) {
+ useAllConstructor = (Boolean) entry.getValue();
+ } else if(name.equals("useExistsConstructor")) {
+ useExistsConstructor = (Boolean) entry.getValue();
+ } else if(name.equals("useHasValueConstructor")) {
+ useHasValueConstructor = (Boolean) entry.getValue();
+ } else if(name.equals("valueFrequencyThreshold")) {
+ valueFrequencyThreshold = (Integer) entry.getValue();
+ } else if(name.equals("useCardinalityRestrictions")) {
+ useCardinalityRestrictions = (Boolean) entry.getValue();
+ } else if(name.equals("useNegation")) {
+ useNegation = (Boolean) entry.getValue();
+ } else if(name.equals("noisePercentage")) {
+ noisePercentage = (Double) entry.getValue();
+ } else if(name.equals("useBooleanDatatypes")) {
+ useBooleanDatatypes = (Boolean) entry.getValue();
+ } else if(name.equals("useDoubleDatatypes")) {
+ useDoubleDatatypes = (Boolean) entry.getValue();
+ } else if(name.equals("usePropernessChecks")) {
+ usePropernessChecks = (Boolean) entry.getValue();
+ } else if(name.equals("maxPosOnlyExpansion")) {
+ maxPosOnlyExpansion = (Integer) entry.getValue();
+ } else if(name.equals("startClass")) {
+ startClass = new NamedClass((String)entry.getValue());
+ }else if(name.equals("maxExecutionTimeInSeconds")) {
+ maxExecutionTimeInSeconds = (Integer) entry.getValue();
+ }else if(name.equals("minExecutionTimeInSeconds")) {
+ minExecutionTimeInSeconds = (Integer) entry.getValue();
+ }else if(name.equals("guaranteeXgoodDescriptions")) {
+ guaranteeXgoodDescriptions = (Integer) entry.getValue();
+ } else if(name.equals("maxClassDescriptionTests")) {
+ maxClassDescriptionTests = (Integer) entry.getValue();
+ } else if(name.equals("logLevel")) {
+ logLevel = ((String)entry.getValue()).toUpperCase();
+ } else if(name.equals("forceRefinementLengthIncrease")) {
+ forceRefinementLengthIncrease = (Boolean) entry.getValue();
+ }
+ }
+
+ /* (non-Javadoc)
+ * @see org.dllearner.core.Component#init()
+ */
+ @Override
+ public void init() throws ComponentInitException {
+
+ // exit with a ComponentInitException if the reasoner is unsupported for this learning algorithm
+ if(reasoner.getReasonerType() == ReasonerType.DIG) {
+ throw new ComponentInitException("DIG does not support the inferences needed in the selected learning algorithm component: " + getName());
+ }
+
+ // set log level if the option has been set
+ if(!logLevel.equals(CommonConfigOptions.logLevelDefault))
+ logger.setLevel(Level.toLevel(logLevel,Level.toLevel(CommonConfigOptions.logLevelDefault)));
+
+ if(searchTreeFile == null)
+ searchTreeFile = new File(defaultSearchTreeFile);
+
+ if(writeSearchTree)
+ Files.clearFile(searchTreeFile);
+
+ // adjust heuristic
+ ExampleBasedHeuristic algHeuristic;
+
+ if(heuristic == "lexicographic")
+ algHeuristic = new LexicographicHeuristic();
+ else if(heuristic == "flexible") {
+ if(learningProblem instanceof PosOnlyLP) {
+ throw new RuntimeException("does not work with positive examples only yet");
+ }
+ algHeuristic = new FlexibleHeuristic(((PosNegLP)learningProblem).getNegativeExamples().size(), ((PosNegLP)learningProblem).getPercentPerLengthUnit());
+ } else {
+ if(learningProblem instanceof PosOnlyLP) {
+// throw new RuntimeException("does not work with positive examples only yet");
+ algHeuristic = new MultiHeuristic(((PosOnlyLP)learningProblem).getPositiveExamples().size(),0, configurator);
+ } else {
+ algHeuristic = new MultiHeuristic(((PosNegLP)learningProblem).getPositiveExamples().size(),((PosNegLP)learningProblem).getNegativeExamples().size(), configurator);
+ }
+ }
+
+ // compute used concepts/roles from allowed/ignored
+ // concepts/roles
+ if(allowedConcepts != null) {
+ // sanity check to control if no non-existing concepts are in the list
+ Helper.checkConcepts(reasoner, allowedConcepts);
+ usedConcepts = allowedConcepts;
+ } else if(ignoredConcepts != null) {
+ usedConcepts = Helper.computeConceptsUsingIgnoreList(reasoner, ignoredConcepts);
+ } else {
+ usedConcepts = Helper.computeConcepts(reasoner);
+ }
+
+ if(allowedRoles != null) {
+ Helper.checkRoles(reasoner, allowedRoles);
+ usedRoles = allowedRoles;
+ } else if(ignoredRoles != null) {
+ Helper.checkRoles(reasoner, ignoredRoles);
+ usedRoles = Helper.difference(reasoner.getObjectProperties(), ignoredRoles);
+ } else {
+ usedRoles = reasoner.getObjectProperties();
+ }
+
+ // prepare subsumption and role hierarchies, because they are needed
+ // during the run of the algorithm;
+ // in contrast to before, the learning algorithms have to maintain their
+ // own view on the class hierarchy
+ ClassHierarchy classHierarchy = reasoner.getClassHierarchy().cloneAndRestrict(usedConcepts);
+ if(improveSubsumptionHierarchy)
+ classHierarchy.thinOutSubsumptionHierarchy();
+
+// System.out.println(classHierarchy);
+// System.exit(0);
+
+// reasoner.prepareRoleHierarchy(usedRoles);
+ // prepare datatype hierarchy only if necessary
+// if(reasoner.hasDatatypeSupport())
+// reasoner.prepareDatatypePropertyHierarchy();
+
+ // create a refinement operator and pass all configuration
+ // variables to it
+// RhoDRDown
+ operator = new RhoDRDown(
+ reasoner,
+ classHierarchy,
+ configurator,
+ applyAllFilter,
+ applyExistsFilter,
+ useAllConstructor,
+ useExistsConstructor,
+ useHasValueConstructor,
+ valueFrequencyThreshold,
+ useCardinalityRestrictions,
+ useNegation,
+ useBooleanDatatypes,
+ useDoubleDatatypes,
+ startClass
+ );
+
+ // create an algorithm object and pass all configuration
+ // options to it
+ algorithm = new ROLearner2(
+ configurator,
+ learningProblem,
+ reasoner,
+ operator,
+ algHeuristic,
+ startClass,
+ // usedConcepts,
+ // usedRoles,
+ noisePercentage/(double)100,
+ writeSearchTree,
+ replaceSearchTree,
+ searchTreeFile,
+ useTooWeakList,
+ useOverlyGeneralList,
+ useShortConceptConstruction,
+ usePropernessChecks,
+ maxPosOnlyExpansion,
+ maxExecutionTimeInSeconds,
+ minExecutionTimeInSeconds,
+ guaranteeXgoodDescriptions,
+ maxClassDescriptionTests,
+ forceRefinementLengthIncrease
+ );
+ // note: used concepts and roles do not need to be passed
+ // as argument, because it is sufficient to prepare the
+ // concept and role hierarchy accordingly
+ }
+
+ public static String getName() {
+// return "refinement operator based learning algorithm II";
+ return "OCEL";
+ }
+
+ public static String getUsage() {
+ return "algorithm = refexamples;";
+ }
+
+ @Override
+ public void start() {
+ algorithm.start();
+ }
+
+// @Override
+ public ScorePosNeg getSolutionScore() {
+ return algorithm.getSolutionScore();
+ }
+
+ @Override
+ public Description getCurrentlyBestDescription() {
+ return algorithm.getBestSolution();
+ }
+
+ @Override
+ public synchronized List<Description> getCurrentlyBestDescriptions() {
+ return algorithm.getCurrentlyBestDescriptions();
+ }
+
+ @Override
+ public EvaluatedDescriptionPosNeg getCurrentlyBestEvaluatedDescription() {
+ return new EvaluatedDescriptionPosNeg(algorithm.getBestSolution(),algorithm.getSolutionScore());
+ }
+
+ @Override
+ public synchronized TreeSet<EvaluatedDescriptionPosNeg> getCurrentlyBestEvaluatedDescriptions() {
+ return algorithm.getCurrentlyBestEvaluatedDescriptions();
+ }
+
+ /** {@inheritDoc} */
+ @Override
+ public void stop() {
+ algorithm.stop();
+ }
+
+ public ExampleBasedNode getStartNode() {
+ return algorithm.getStartNode();
+ }
+
+ /** {@inheritDoc} */
+ @Override
+ public void pause() {
+ // TODO: not implemented
+ }
+
+ /** {@inheritDoc} */
+ @Override
+ public void resume() {
+ // TODO: not implemented
+ }
+
+ /* (non-Javadoc)
+ * @see org.dllearner.core.LearningAlgorithm#isRunning()
+ */
+ /** {@inheritDoc} */
+ @Override
+ public boolean isRunning() {
+ return algorithm.isRunning();
+ }
+
+ public RhoDRDown getRefinementOperator() {
+ return operator;
+ }
+}
Deleted: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ROLComponent2.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/ROLComponent2.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ROLComponent2.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -1,503 +0,0 @@
-/**
- * Copyright (C) 2007-2008, Jens Lehmann
- *
- * This file is part of DL-Learner.
- *
- * DL-Learner is free software; you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation; either version 3 of the License, or
- * (at your option) any later version.
- *
- * DL-Learner is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with this program. If not, see <http://www.gnu.org/licenses/>.
- *
- */
-
-package org.dllearner.algorithms.refinement2;
-
-import java.io.File;
-import java.util.Collection;
-import java.util.LinkedList;
-import java.util.List;
-import java.util.Set;
-import java.util.TreeSet;
-
-import org.apache.log4j.Level;
-import org.apache.log4j.Logger;
-import org.dllearner.core.ComponentInitException;
-import org.dllearner.core.LearningAlgorithm;
-import org.dllearner.core.LearningProblem;
-import org.dllearner.core.ReasonerComponent;
-import org.dllearner.core.configurators.ROLComponent2Configurator;
-import org.dllearner.core.options.BooleanConfigOption;
-import org.dllearner.core.options.CommonConfigMappings;
-import org.dllearner.core.options.CommonConfigOptions;
-import org.dllearner.core.options.ConfigEntry;
-import org.dllearner.core.options.ConfigOption;
-import org.dllearner.core.options.DoubleConfigOption;
-import org.dllearner.core.options.IntegerConfigOption;
-import org.dllearner.core.options.InvalidConfigOptionValueException;
-import org.dllearner.core.options.StringConfigOption;
-import org.dllearner.core.owl.ClassHierarchy;
-import org.dllearner.core.owl.Description;
-import org.dllearner.core.owl.NamedClass;
-import org.dllearner.core.owl.ObjectProperty;
-import org.dllearner.learningproblems.EvaluatedDescriptionPosNeg;
-import org.dllearner.learningproblems.PosNegLP;
-import org.dllearner.learningproblems.PosOnlyLP;
-import org.dllearner.learningproblems.ScorePosNeg;
-import org.dllearner.reasoning.ReasonerType;
-import org.dllearner.refinementoperators.RhoDRDown;
-import org.dllearner.utilities.Files;
-import org.dllearner.utilities.Helper;
-
-/**
- * The DL-Learner learning algorithm component for the example
- * based refinement operator approach. It handles all
- * configuration options, creates the corresponding objects and
- * passes them to the actual refinement operator, heuristic, and
- * learning algorithm implementations.
- *
- * Note: The options supported by the ROLearner component and this
- * one are not equal. Options that have been dropped for now:
- * - horizontal expansion factor: The goal of the algorithm will
- * be to (hopefully) be able to learn long and complex concepts
- * more efficiently.
- * A horizontal expansion factor has its benefits, but limits
- * the length of concepts learnable in reasonable time to
- * about 15 with its default value of 0.6 and a small sized
- * background knowledge base. We hope to get more fine-grained
- * control of whether it makes sense to extend a node with
- * more sophisticated heuristics.
- * Dropping the horizontal expansion factor means that the
- * completeness of the algorithm depends on the heuristic.
- *
- * @author Jens Lehmann
- *
- */
-public class ROLComponent2 extends LearningAlgorithm {
-
- private ROLComponent2Configurator configurator;
- @Override
- public ROLComponent2Configurator getConfigurator(){
- return configurator;
- }
-
- // actual algorithm
- private ROLearner2 algorithm;
- private static Logger logger = Logger
- .getLogger(ROLComponent2.class);
- private String logLevel = CommonConfigOptions.logLevelDefault;
- RhoDRDown operator;
-
- // configuration options
- private boolean writeSearchTree;
- private File searchTreeFile;
- private boolean replaceSearchTree = false;
- private static String defaultSearchTreeFile = "log/searchTree.txt";
- private String heuristic = "multi";
- Set<NamedClass> allowedConcepts;
- Set<ObjectProperty> allowedRoles;
- Set<NamedClass> ignoredConcepts;
- Set<ObjectProperty> ignoredRoles;
- // these are computed as the result of the previous four settings
- Set<NamedClass> usedConcepts;
- Set<ObjectProperty> usedRoles;
- private boolean applyAllFilter = true;
- private boolean applyExistsFilter = true;
- private boolean useTooWeakList = true;
- private boolean useOverlyGeneralList = true;
- private boolean useShortConceptConstruction = true;
- private boolean improveSubsumptionHierarchy = true;
- private boolean useAllConstructor = CommonConfigOptions.useAllConstructorDefault;
- private boolean useExistsConstructor = CommonConfigOptions.useExistsConstructorDefault;
- private boolean useHasValueConstructor = CommonConfigOptions.useHasValueConstructorDefault;
- private int valueFrequencyThreshold = CommonConfigOptions.valueFrequencyThresholdDefault;
- private boolean useCardinalityRestrictions = CommonConfigOptions.useCardinalityRestrictionsDefault;
- private boolean useNegation = CommonConfigOptions.useNegationDefault;
- private boolean useBooleanDatatypes = CommonConfigOptions.useBooleanDatatypesDefault;
- private boolean useDoubleDatatypes = CommonConfigOptions.useDoubleDatatypesDefault;
- private static double noisePercentageDefault = 0.0;
- private double noisePercentage = noisePercentageDefault;
- private NamedClass startClass = null;
- //refactor this
- private static boolean usePropernessChecksDefault = false;
- private boolean usePropernessChecks = usePropernessChecksDefault;
- // refactor this
- private static int maxPosOnlyExpansionDefault = 4;
- private int maxPosOnlyExpansion = maxPosOnlyExpansionDefault;
- private boolean forceRefinementLengthIncrease = true;
- //extended Options
- //in seconds
- private int maxExecutionTimeInSeconds = CommonConfigOptions.maxExecutionTimeInSecondsDefault;
- private int minExecutionTimeInSeconds = CommonConfigOptions.minExecutionTimeInSecondsDefault;
- private int guaranteeXgoodDescriptions = CommonConfigOptions.guaranteeXgoodDescriptionsDefault;
- private int maxClassDescriptionTests = CommonConfigOptions.maxClassDescriptionTestsDefault;
-
- // Variablen zur Einstellung der Protokollierung
- // boolean quiet = false;
- boolean showBenchmarkInformation = false;
- // boolean createTreeString = false;
- // String searchTree = new String();
-
- // Konfiguration des Algorithmus
- // Faktor für horizontale Erweiterung (notwendig für completeness)
- // double horizontalExpansionFactor = 0.6;
-
- // soll später einen Operator und eine Heuristik entgegennehmen
- // public ROLearner(LearningProblem learningProblem, LearningProblem learningProblem2) {
- public ROLComponent2(PosNegLP learningProblem, ReasonerComponent reasoningService) {
- super(learningProblem, reasoningService);
- this.configurator = new ROLComponent2Configurator(this);
- }
-
- public ROLComponent2(PosOnlyLP learningProblem, ReasonerComponent reasoningService) {
- super(learningProblem, reasoningService);
- this.configurator = new ROLComponent2Configurator(this);
- }
-
- public static Collection<Class<? extends LearningProblem>> supportedLearningProblems() {
- Collection<Class<? extends LearningProblem>> problems = new LinkedList<Class<? extends LearningProblem>>();
- problems.add(PosNegLP.class);
- problems.add(PosOnlyLP.class);
- return problems;
- }
-
- public static Collection<ConfigOption<?>> createConfigOptions() {
- Collection<ConfigOption<?>> options = new LinkedList<ConfigOption<?>>();
- options.add(new BooleanConfigOption("writeSearchTree", "specifies whether to write a search tree", false));
- options.add(new StringConfigOption("searchTreeFile","file to use for the search tree", defaultSearchTreeFile));
- options.add(new BooleanConfigOption("replaceSearchTree","specifies whether to replace the search tree in the log file after each run or append the new search tree", false));
- StringConfigOption heuristicOption = new StringConfigOption("heuristic", "specifiy the heuristic to use", "lexicographic");
- heuristicOption.setAllowedValues(new String[] {"lexicographic", "flexible"});
- options.add(heuristicOption);
- options.add(new BooleanConfigOption("applyAllFilter", "usage of equivalence ALL R.C AND ALL R.D = ALL R.(C AND D)", true));
- options.add(new BooleanConfigOption("applyExistsFilter", "usage of equivalence EXISTS R.C OR EXISTS R.D = EXISTS R.(C OR D)", true));
- options.add(new BooleanConfigOption("useTooWeakList", "try to filter out too weak concepts without sending them to the reasoner", true));
- options.add(new BooleanConfigOption("useOverlyGeneralList", "try to find overly general concept without sending them to the reasoner", true));
- options.add(new BooleanConfigOption("useShortConceptConstruction", "shorten concept to see whether they already exist", true));
- DoubleConfigOption horizExp = new DoubleConfigOption("horizontalExpansionFactor", "horizontal expansion factor (see publication for description)", 0.6);
- horizExp.setLowerLimit(0.0);
- horizExp.setUpperLimit(1.0);
- options.add(horizExp);
- options.add(new BooleanConfigOption("improveSubsumptionHierarchy", "simplify subsumption hierarchy to reduce search space (see publication for description)", true));
- options.add(CommonConfigOptions.allowedConcepts());
- options.add(CommonConfigOptions.ignoredConcepts());
- // allowed/ignored roles are an unstable/untested feature
- options.add(CommonConfigOptions.allowedRoles());
- options.add(CommonConfigOptions.ignoredRoles());
- options.add(CommonConfigOptions.useAllConstructor());
- options.add(CommonConfigOptions.useExistsConstructor());
- options.add(CommonConfigOptions.useHasValueConstructor());
- options.add(CommonConfigOptions.useDataHasValueConstructor());
- options.add(CommonConfigOptions.valueFreqencyThreshold());
- options.add(CommonConfigOptions.useCardinalityRestrictions());
- options.add(CommonConfigOptions.cardinalityLimit());
- options.add(CommonConfigOptions.useNegation());
- options.add(CommonConfigOptions.useBooleanDatatypes());
- options.add(CommonConfigOptions.useDoubleDatatypes());
- options.add(CommonConfigOptions.useStringDatatypes());
- options.add(CommonConfigOptions.maxExecutionTimeInSeconds());
- options.add(CommonConfigOptions.minExecutionTimeInSeconds());
- options.add(CommonConfigOptions.guaranteeXgoodDescriptions());
- options.add(CommonConfigOptions.maxClassDescriptionTests());
- options.add(CommonConfigOptions.getLogLevel());
- options.add(new BooleanConfigOption("usePropernessChecks", "specifies whether to check for equivalence (i.e. discard equivalent refinements)",usePropernessChecksDefault));
- options.add(CommonConfigOptions.getNoisePercentage());
- options.add(CommonConfigOptions.getTerminateOnNoiseReached());
- options.add(new StringConfigOption("startClass", "the named class which should be used to start the algorithm (GUI: needs a widget for selecting a class)"));
- options.add(new BooleanConfigOption("forceRefinementLengthIncrease", "specifies whether nodes should be expanded until only longer refinements are reached"));
- options.add(new DoubleConfigOption("negativeWeight", "Used to penalise errors on negative examples different from those of positive examples (lower = less importance for negatives).",1.0));
- options.add(new DoubleConfigOption("startNodeBonus", "You can use this to give a heuristic bonus on the start node (= initially broader exploration of search space).",0.0));
- options.add(new IntegerConfigOption("negationPenalty", "Penalty on negations (TODO: better explanation).", 0));
- options.add(CommonConfigOptions.getExpansionPenaltyFactor(0.02));
- options.add(CommonConfigOptions.getInstanceBasedDisjoints());
- return options;
- }
-
- /* (non-Javadoc)
- * @see org.dllearner.core.Component#applyConfigEntry(org.dllearner.core.ConfigEntry)
- */
- @Override
- @SuppressWarnings({"unchecked"})
- public <T> void applyConfigEntry(ConfigEntry<T> entry) throws InvalidConfigOptionValueException {
- String name = entry.getOptionName();
- if(name.equals("writeSearchTree"))
- writeSearchTree = (Boolean) entry.getValue();
- else if(name.equals("searchTreeFile"))
- searchTreeFile = new File((String)entry.getValue());
- else if(name.equals("replaceSearchTree"))
- replaceSearchTree = (Boolean) entry.getValue();
- else if(name.equals("heuristic")) {
- String value = (String) entry.getValue();
- if(value.equals("lexicographic"))
- heuristic = "lexicographic";
- else
- heuristic = "flexible";
- } else if(name.equals("allowedConcepts")) {
- allowedConcepts = CommonConfigMappings.getAtomicConceptSet((Set<String>)entry.getValue());
- } else if(name.equals("allowedRoles")) {
- allowedRoles = CommonConfigMappings.getAtomicRoleSet((Set<String>)entry.getValue());
- } else if(name.equals("ignoredConcepts")) {
- ignoredConcepts = CommonConfigMappings.getAtomicConceptSet((Set<String>)entry.getValue());
- } else if(name.equals("ignoredRoles")) {
- ignoredRoles = CommonConfigMappings.getAtomicRoleSet((Set<String>)entry.getValue());
- } else if(name.equals("applyAllFilter")) {
- applyAllFilter = (Boolean) entry.getValue();
- } else if(name.equals("applyExistsFilter")) {
- applyExistsFilter = (Boolean) entry.getValue();
- } else if(name.equals("useTooWeakList")) {
- useTooWeakList = (Boolean) entry.getValue();
- } else if(name.equals("useOverlyGeneralList")) {
- useOverlyGeneralList = (Boolean) entry.getValue();
- } else if(name.equals("useShortConceptConstruction")) {
- useShortConceptConstruction = (Boolean) entry.getValue();
- } else if(name.equals("improveSubsumptionHierarchy")) {
- improveSubsumptionHierarchy = (Boolean) entry.getValue();
- } else if(name.equals("useAllConstructor")) {
- useAllConstructor = (Boolean) entry.getValue();
- } else if(name.equals("useExistsConstructor")) {
- useExistsConstructor = (Boolean) entry.getValue();
- } else if(name.equals("useHasValueConstructor")) {
- useHasValueConstructor = (Boolean) entry.getValue();
- } else if(name.equals("valueFrequencyThreshold")) {
- valueFrequencyThreshold = (Integer) entry.getValue();
- } else if(name.equals("useCardinalityRestrictions")) {
- useCardinalityRestrictions = (Boolean) entry.getValue();
- } else if(name.equals("useNegation")) {
- useNegation = (Boolean) entry.getValue();
- } else if(name.equals("noisePercentage")) {
- noisePercentage = (Double) entry.getValue();
- } else if(name.equals("useBooleanDatatypes")) {
- useBooleanDatatypes = (Boolean) entry.getValue();
- } else if(name.equals("useDoubleDatatypes")) {
- useDoubleDatatypes = (Boolean) entry.getValue();
- } else if(name.equals("usePropernessChecks")) {
- usePropernessChecks = (Boolean) entry.getValue();
- } else if(name.equals("maxPosOnlyExpansion")) {
- maxPosOnlyExpansion = (Integer) entry.getValue();
- } else if(name.equals("startClass")) {
- startClass = new NamedClass((String)entry.getValue());
- }else if(name.equals("maxExecutionTimeInSeconds")) {
- maxExecutionTimeInSeconds = (Integer) entry.getValue();
- }else if(name.equals("minExecutionTimeInSeconds")) {
- minExecutionTimeInSeconds = (Integer) entry.getValue();
- }else if(name.equals("guaranteeXgoodDescriptions")) {
- guaranteeXgoodDescriptions = (Integer) entry.getValue();
- } else if(name.equals("maxClassDescriptionTests")) {
- maxClassDescriptionTests = (Integer) entry.getValue();
- } else if(name.equals("logLevel")) {
- logLevel = ((String)entry.getValue()).toUpperCase();
- } else if(name.equals("forceRefinementLengthIncrease")) {
- forceRefinementLengthIncrease = (Boolean) entry.getValue();
- }
- }
-
- /* (non-Javadoc)
- * @see org.dllearner.core.Component#init()
- */
- @Override
- public void init() throws ComponentInitException {
-
- // exit with a ComponentInitException if the reasoner is unsupported for this learning algorithm
- if(reasoner.getReasonerType() == ReasonerType.DIG) {
- throw new ComponentInitException("DIG does not support the inferences needed in the selected learning algorithm component: " + getName());
- }
-
- // set log level if the option has been set
- if(!logLevel.equals(CommonConfigOptions.logLevelDefault))
- logger.setLevel(Level.toLevel(logLevel,Level.toLevel(CommonConfigOptions.logLevelDefault)));
-
- if(searchTreeFile == null)
- searchTreeFile = new File(defaultSearchTreeFile);
-
- if(writeSearchTree)
- Files.clearFile(searchTreeFile);
-
- // adjust heuristic
- ExampleBasedHeuristic algHeuristic;
-
- if(heuristic == "lexicographic")
- algHeuristic = new LexicographicHeuristic();
- else if(heuristic == "flexible") {
- if(learningProblem instanceof PosOnlyLP) {
- throw new RuntimeException("does not work with positive examples only yet");
- }
- algHeuristic = new FlexibleHeuristic(((PosNegLP)learningProblem).getNegativeExamples().size(), ((PosNegLP)learningProblem).getPercentPerLengthUnit());
- } else {
- if(learningProblem instanceof PosOnlyLP) {
-// throw new RuntimeException("does not work with positive examples only yet");
- algHeuristic = new MultiHeuristic(((PosOnlyLP)learningProblem).getPositiveExamples().size(),0, configurator);
- } else {
- algHeuristic = new MultiHeuristic(((PosNegLP)learningProblem).getPositiveExamples().size(),((PosNegLP)learningProblem).getNegativeExamples().size(), configurator);
- }
- }
-
- // compute used concepts/roles from allowed/ignored
- // concepts/roles
- if(allowedConcepts != null) {
- // sanity check to control if no non-existing concepts are in the list
- Helper.checkConcepts(reasoner, allowedConcepts);
- usedConcepts = allowedConcepts;
- } else if(ignoredConcepts != null) {
- usedConcepts = Helper.computeConceptsUsingIgnoreList(reasoner, ignoredConcepts);
- } else {
- usedConcepts = Helper.computeConcepts(reasoner);
- }
-
- if(allowedRoles != null) {
- Helper.checkRoles(reasoner, allowedRoles);
- usedRoles = allowedRoles;
- } else if(ignoredRoles != null) {
- Helper.checkRoles(reasoner, ignoredRoles);
- usedRoles = Helper.difference(reasoner.getObjectProperties(), ignoredRoles);
- } else {
- usedRoles = reasoner.getObjectProperties();
- }
-
- // prepare subsumption and role hierarchies, because they are needed
- // during the run of the algorithm;
- // in contrast to before, the learning algorithms have to maintain their
- // own view on the class hierarchy
- ClassHierarchy classHierarchy = reasoner.getClassHierarchy().cloneAndRestrict(usedConcepts);
- if(improveSubsumptionHierarchy)
- classHierarchy.thinOutSubsumptionHierarchy();
-
-// System.out.println(classHierarchy);
-// System.exit(0);
-
-// reasoner.prepareRoleHierarchy(usedRoles);
- // prepare datatype hierarchy only if necessary
-// if(reasoner.hasDatatypeSupport())
-// reasoner.prepareDatatypePropertyHierarchy();
-
- // create a refinement operator and pass all configuration
- // variables to it
-// RhoDRDown
- operator = new RhoDRDown(
- reasoner,
- classHierarchy,
- configurator,
- applyAllFilter,
- applyExistsFilter,
- useAllConstructor,
- useExistsConstructor,
- useHasValueConstructor,
- valueFrequencyThreshold,
- useCardinalityRestrictions,
- useNegation,
- useBooleanDatatypes,
- useDoubleDatatypes,
- startClass
- );
-
- // create an algorithm object and pass all configuration
- // options to it
- algorithm = new ROLearner2(
- configurator,
- learningProblem,
- reasoner,
- operator,
- algHeuristic,
- startClass,
- // usedConcepts,
- // usedRoles,
- noisePercentage/(double)100,
- writeSearchTree,
- replaceSearchTree,
- searchTreeFile,
- useTooWeakList,
- useOverlyGeneralList,
- useShortConceptConstruction,
- usePropernessChecks,
- maxPosOnlyExpansion,
- maxExecutionTimeInSeconds,
- minExecutionTimeInSeconds,
- guaranteeXgoodDescriptions,
- maxClassDescriptionTests,
- forceRefinementLengthIncrease
- );
- // note: used concepts and roles do not need to be passed
- // as argument, because it is sufficient to prepare the
- // concept and role hierarchy accordingly
- }
-
- public static String getName() {
-// return "refinement operator based learning algorithm II";
- return "OCEL";
- }
-
- public static String getUsage() {
- return "algorithm = refexamples;";
- }
-
- @Override
- public void start() {
- algorithm.start();
- }
-
-// @Override
- public ScorePosNeg getSolutionScore() {
- return algorithm.getSolutionScore();
- }
-
- @Override
- public Description getCurrentlyBestDescription() {
- return algorithm.getBestSolution();
- }
-
- @Override
- public synchronized List<Description> getCurrentlyBestDescriptions() {
- return algorithm.getCurrentlyBestDescriptions();
- }
-
- @Override
- public EvaluatedDescriptionPosNeg getCurrentlyBestEvaluatedDescription() {
- return new EvaluatedDescriptionPosNeg(algorithm.getBestSolution(),algorithm.getSolutionScore());
- }
-
- @Override
- public synchronized TreeSet<EvaluatedDescriptionPosNeg> getCurrentlyBestEvaluatedDescriptions() {
- return algorithm.getCurrentlyBestEvaluatedDescriptions();
- }
-
- /** {@inheritDoc} */
- @Override
- public void stop() {
- algorithm.stop();
- }
-
- public ExampleBasedNode getStartNode() {
- return algorithm.getStartNode();
- }
-
- /** {@inheritDoc} */
- @Override
- public void pause() {
- // TODO: not implemented
- }
-
- /** {@inheritDoc} */
- @Override
- public void resume() {
- // TODO: not implemented
- }
-
- /* (non-Javadoc)
- * @see org.dllearner.core.LearningAlgorithm#isRunning()
- */
- /** {@inheritDoc} */
- @Override
- public boolean isRunning() {
- return algorithm.isRunning();
- }
-
- public RhoDRDown getRefinementOperator() {
- return operator;
- }
-}
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ROLearner2.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/ROLearner2.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/ROLearner2.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -17,7 +17,7 @@
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
*/
-package org.dllearner.algorithms.refinement2;
+package org.dllearner.algorithms.ocel;
import java.io.File;
import java.text.DecimalFormat;
@@ -290,7 +290,7 @@
evaluateSetCreationTimeNs = 0;
improperConceptsRemovalTimeNs = 0;
- Monitor totalLearningTime = JamonMonitorLogger.getTimeMonitor(ROLComponent2.class, "totalLearningTime")
+ Monitor totalLearningTime = JamonMonitorLogger.getTimeMonitor(OCEL.class, "totalLearningTime")
.start();
// TODO: write a JUnit test for this problem (long-lasting or infinite
// loops because
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/SubsumptionComparator.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement2/SubsumptionComparator.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/SubsumptionComparator.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -1,4 +1,4 @@
-package org.dllearner.algorithms.refinement2;
+package org.dllearner.algorithms.ocel;
import java.util.Comparator;
Modified: trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -97,7 +97,7 @@
"org.dllearner.algorithms.RandomGuesser",
"org.dllearner.algorithms.BruteForceLearner",
"org.dllearner.algorithms.refinement.ROLearner",
- "org.dllearner.algorithms.refinement2.ROLComponent2",
+ "org.dllearner.algorithms.ocel.OCEL",
"org.dllearner.algorithms.gp.GP",
"org.dllearner.algorithms.el.ELLearningAlgorithm",
"org.dllearner.algorithms.el.ELLearningAlgorithmDisjunctive",
Modified: trunk/components-core/src/main/java/org/dllearner/core/configurators/ComponentFactory.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/configurators/ComponentFactory.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/core/configurators/ComponentFactory.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -29,8 +29,8 @@
import org.dllearner.algorithms.el.ELLearningAlgorithmDisjunctive;
import org.dllearner.algorithms.gp.GP;
import org.dllearner.algorithms.isle.ISLE;
+import org.dllearner.algorithms.ocel.OCEL;
import org.dllearner.algorithms.refinement.ROLearner;
-import org.dllearner.algorithms.refinement2.ROLComponent2;
import org.dllearner.core.KnowledgeSource;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.LearningProblemUnsupportedException;
@@ -261,7 +261,7 @@
* @throws LearningProblemUnsupportedException see
* @return a component ready for initialization ROLComponent2
**/
-public static ROLComponent2 getROLComponent2(LearningProblem learningProblem, ReasonerComponent reasoningService) throws LearningProblemUnsupportedException {
+public static OCEL getROLComponent2(LearningProblem learningProblem, ReasonerComponent reasoningService) throws LearningProblemUnsupportedException {
return ROLComponent2Configurator.getROLComponent2(learningProblem, reasoningService);
}
Modified: trunk/components-core/src/main/java/org/dllearner/core/configurators/ROLComponent2Configurator.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/configurators/ROLComponent2Configurator.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/core/configurators/ROLComponent2Configurator.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -21,7 +21,8 @@
package org.dllearner.core.configurators;
import java.util.Set;
-import org.dllearner.algorithms.refinement2.ROLComponent2;
+
+import org.dllearner.algorithms.ocel.OCEL;
import org.dllearner.core.ComponentManager;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.LearningProblemUnsupportedException;
@@ -36,12 +37,12 @@
public class ROLComponent2Configurator extends RefinementOperatorConfigurator implements Configurator {
private boolean reinitNecessary = false;
-private ROLComponent2 rOLComponent2;
+private OCEL rOLComponent2;
/**
* @param rOLComponent2 see ROLComponent2
**/
-public ROLComponent2Configurator(ROLComponent2 rOLComponent2){
+public ROLComponent2Configurator(OCEL rOLComponent2){
this.rOLComponent2 = rOLComponent2;
}
@@ -51,8 +52,8 @@
* @throws LearningProblemUnsupportedException see
* @return ROLComponent2
**/
-public static ROLComponent2 getROLComponent2(LearningProblem learningProblem, ReasonerComponent reasoningService) throws LearningProblemUnsupportedException{
-ROLComponent2 component = ComponentManager.getInstance().learningAlgorithm(ROLComponent2.class, learningProblem, reasoningService);
+public static OCEL getROLComponent2(LearningProblem learningProblem, ReasonerComponent reasoningService) throws LearningProblemUnsupportedException{
+OCEL component = ComponentManager.getInstance().learningAlgorithm(OCEL.class, learningProblem, reasoningService);
return component;
}
Modified: trunk/components-core/src/main/java/org/dllearner/examples/KRKModular.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/examples/KRKModular.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/examples/KRKModular.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -15,7 +15,7 @@
import java.util.StringTokenizer;
import java.util.TreeSet;
-import org.dllearner.algorithms.refinement2.ROLComponent2;
+import org.dllearner.algorithms.ocel.OCEL;
import org.dllearner.core.ComponentManager;
import org.dllearner.core.KnowledgeSource;
import org.dllearner.core.LearningAlgorithm;
@@ -265,7 +265,7 @@
lp.init();
- la = cm.learningAlgorithm(ROLComponent2.class, lp, r);
+ la = cm.learningAlgorithm(OCEL.class, lp, r);
SortedSet<String> ignoredConcepts = getIgnoredConcepts(pos, neg);
cm.applyConfigEntry(la,"useAllConstructor",false);
Modified: trunk/components-core/src/main/java/org/dllearner/utilities/JamonMonitorLogger.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/utilities/JamonMonitorLogger.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/utilities/JamonMonitorLogger.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -26,7 +26,7 @@
import java.util.SortedSet;
import java.util.TreeSet;
-import org.dllearner.algorithms.refinement2.ROLComponent2;
+import org.dllearner.algorithms.ocel.OCEL;
import org.dllearner.kb.extraction.ExtractionAlgorithm;
import org.dllearner.kb.manipulator.Manipulator;
import org.dllearner.kb.manipulator.TypeFilterRule;
@@ -127,7 +127,7 @@
retval= "sparql:";
} else if (clazz == SparqlQuery.class) {
retval= "sparql:";
- } else if (clazz == ROLComponent2.class) {
+ } else if (clazz == OCEL.class) {
retval= "Learning:";
} else if (clazz == SparqlQuery.class) {
retval= "sparql:";
Modified: trunk/components-core/src/main/java/org/dllearner/utilities/components/ComponentCombo.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/utilities/components/ComponentCombo.java 2010-09-21 19:25:30 UTC (rev 2333)
+++ trunk/components-core/src/main/java/org/dllearner/utilities/components/ComponentCombo.java 2010-09-24 09:26:02 UTC (rev 2334)
@@ -23,7 +23,7 @@
import java.util.HashSet;
import java.util.Set;
-import org.dllearner.algorithms.refinement2.ROLComponent2;
+import org.dllearner.algorith...
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