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[DL-Learner SVN] SF.net SVN: dl-learner: [986] trunk/src/dl-learner/org/dllearner
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From: <jen...@us...> - 2008-06-27 14:28:52
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Revision: 986
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=986&view=rev
Author: jenslehmann
Date: 2008-06-27 07:28:48 -0700 (Fri, 27 Jun 2008)
Log Message:
-----------
extension of abstract LearningAlgorithm class and many subsequent (possibly code-breaking) changes
Modified Paths:
--------------
trunk/src/dl-learner/org/dllearner/algorithms/BruteForceLearner.java
trunk/src/dl-learner/org/dllearner/algorithms/DBpediaNavigationSuggestor.java
trunk/src/dl-learner/org/dllearner/algorithms/RandomGuesser.java
trunk/src/dl-learner/org/dllearner/algorithms/SimpleSuggestionLearningAlgorithm.java
trunk/src/dl-learner/org/dllearner/algorithms/gp/GP.java
trunk/src/dl-learner/org/dllearner/algorithms/refexamples/ExampleBasedROLComponent.java
trunk/src/dl-learner/org/dllearner/algorithms/refexamples/ExampleBasedROLearner.java
trunk/src/dl-learner/org/dllearner/algorithms/refinement/ROLearner.java
trunk/src/dl-learner/org/dllearner/core/LearningAlgorithm.java
trunk/src/dl-learner/org/dllearner/core/Score.java
trunk/src/dl-learner/org/dllearner/examples/KRKModular.java
trunk/src/dl-learner/org/dllearner/gui/MiniGUI.java
trunk/src/dl-learner/org/dllearner/gui/RunPanel.java
trunk/src/dl-learner/org/dllearner/learningproblems/ScoreThreeValued.java
trunk/src/dl-learner/org/dllearner/learningproblems/ScoreTwoValued.java
trunk/src/dl-learner/org/dllearner/scripts/CrossValidation.java
trunk/src/dl-learner/org/dllearner/scripts/SKOS7030.java
trunk/src/dl-learner/org/dllearner/scripts/TestValidation.java
trunk/src/dl-learner/org/dllearner/server/DLLearnerWS.java
trunk/src/dl-learner/org/dllearner/test/ComponentTest.java
trunk/src/dl-learner/org/dllearner/tools/ore/LearningPanelDescriptor.java
trunk/src/dl-learner/org/dllearner/tools/ore/ORE.java
trunk/src/dl-learner/org/dllearner/tools/protege/DLLearnerModel.java
trunk/src/dl-learner/org/dllearner/utilities/owl/ConceptTransformation.java
Added Paths:
-----------
trunk/src/dl-learner/org/dllearner/core/EvaluatedDescription.java
Modified: trunk/src/dl-learner/org/dllearner/algorithms/BruteForceLearner.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/BruteForceLearner.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/algorithms/BruteForceLearner.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -26,6 +26,7 @@
import java.util.List;
import java.util.Map;
+import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.LearningAlgorithm;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasoningService;
@@ -277,8 +278,13 @@
}
@Override
- public Description getBestSolution() {
+ public Description getCurrentlyBestDescription() {
return bestDefinition;
+ }
+
+ @Override
+ public EvaluatedDescription getCurrentlyBestEvaluatedDescription() {
+ return new EvaluatedDescription(bestDefinition,bestScore);
}
@Override
@@ -286,4 +292,22 @@
stop = true;
}
+ /* (non-Javadoc)
+ * @see org.dllearner.core.LearningAlgorithm#pause()
+ */
+ @Override
+ public void pause() {
+ // TODO Auto-generated method stub
+
+ }
+
+ /* (non-Javadoc)
+ * @see org.dllearner.core.LearningAlgorithm#resume()
+ */
+ @Override
+ public void resume() {
+ // TODO Auto-generated method stub
+
+ }
+
}
Modified: trunk/src/dl-learner/org/dllearner/algorithms/DBpediaNavigationSuggestor.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/DBpediaNavigationSuggestor.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/algorithms/DBpediaNavigationSuggestor.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -24,6 +24,7 @@
import org.dllearner.algorithms.refexamples.ExampleBasedROLComponent;
import org.dllearner.core.ComponentInitException;
+import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.LearningAlgorithm;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasoningService;
@@ -145,12 +146,35 @@
}
@Override
- public Description getBestSolution() {
- return learner.getBestSolution();
+ public Description getCurrentlyBestDescription() {
+ return learner.getCurrentlyBestDescription();
+ }
+
+ @Override
+ public EvaluatedDescription getCurrentlyBestEvaluatedDescription() {
+ return learner.getCurrentlyBestEvaluatedDescription();
}
@Override
public Score getSolutionScore() {
return learner.getSolutionScore();
}
+
+ /* (non-Javadoc)
+ * @see org.dllearner.core.LearningAlgorithm#pause()
+ */
+ @Override
+ public void pause() {
+ // TODO Auto-generated method stub
+
+ }
+
+ /* (non-Javadoc)
+ * @see org.dllearner.core.LearningAlgorithm#resume()
+ */
+ @Override
+ public void resume() {
+ // TODO Auto-generated method stub
+
+ }
}
Modified: trunk/src/dl-learner/org/dllearner/algorithms/RandomGuesser.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/RandomGuesser.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/algorithms/RandomGuesser.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -25,6 +25,7 @@
import org.apache.log4j.Logger;
import org.dllearner.algorithms.gp.Program;
import org.dllearner.algorithms.gp.GPUtilities;
+import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.LearningAlgorithm;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasoningService;
@@ -117,8 +118,13 @@
}
@Override
- public Description getBestSolution() {
+ public Description getCurrentlyBestDescription() {
return bestDefinition;
+ }
+
+ @Override
+ public EvaluatedDescription getCurrentlyBestEvaluatedDescription() {
+ return new EvaluatedDescription(bestDefinition,bestScore);
}
@Override
Modified: trunk/src/dl-learner/org/dllearner/algorithms/SimpleSuggestionLearningAlgorithm.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/SimpleSuggestionLearningAlgorithm.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/algorithms/SimpleSuggestionLearningAlgorithm.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -1,9 +1,8 @@
package org.dllearner.algorithms;
-import java.util.Set;
-import java.util.List;
import java.util.*;
+import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.LearningAlgorithm;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasoningService;
@@ -25,9 +24,14 @@
//this.learningProblem = learningProblem;
}
- public Description getBestSolution()
+ public Description getCurrentlyBestDescription()
{
return bestSollution;
+ }
+
+ public EvaluatedDescription getCurrentlyBestEvaluatedDescription()
+ {
+ return new EvaluatedDescription(bestSollution, solutionScore);
}
Modified: trunk/src/dl-learner/org/dllearner/algorithms/gp/GP.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/gp/GP.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/algorithms/gp/GP.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -30,6 +30,7 @@
import java.util.Map.Entry;
import org.dllearner.algorithms.hybridgp.Psi;
+import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.LearningAlgorithm;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasoningService;
@@ -948,9 +949,14 @@
}
@Override
- public Description getBestSolution() {
+ public Description getCurrentlyBestDescription() {
+ return bestConcept;
+ }
+
+ @Override
+ public EvaluatedDescription getCurrentlyBestEvaluatedDescription() {
// return fittestIndividual.getTree();
- return bestConcept;
+ return new EvaluatedDescription(bestConcept,bestScore);
}
@Override
Modified: trunk/src/dl-learner/org/dllearner/algorithms/refexamples/ExampleBasedROLComponent.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/refexamples/ExampleBasedROLComponent.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/algorithms/refexamples/ExampleBasedROLComponent.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -25,9 +25,11 @@
import java.util.LinkedList;
import java.util.List;
import java.util.Set;
+import java.util.SortedSet;
import org.apache.log4j.Level;
import org.apache.log4j.Logger;
+import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.LearningAlgorithm;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasoningService;
@@ -391,21 +393,24 @@
}
@Override
- public Description getBestSolution() {
+ public Description getCurrentlyBestDescription() {
return algorithm.getBestSolution();
}
@Override
- public synchronized List<Description> getBestSolutions(int nrOfSolutions) {
- return algorithm.getBestSolutions(nrOfSolutions);
+ public synchronized SortedSet<Description> getCurrentlyBestDescriptions() {
+ return algorithm.getCurrentlyBestDescriptions();
}
@Override
- public synchronized List<Description> getGoodSolutions() {
- return algorithm.getGoodSolutions();
+ public EvaluatedDescription getCurrentlyBestEvaluatedDescription() {
+ return new EvaluatedDescription(algorithm.getBestSolution(),algorithm.getSolutionScore());
}
-
+ @Override
+ public synchronized SortedSet<EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions() {
+ return algorithm.getCurrentlyBestEvaluatedDescriptions();
+ }
@Override
public void stop() {
@@ -415,14 +420,15 @@
public ExampleBasedNode getStartNode() {
return algorithm.getStartNode();
}
+
+ @Override
+ public void pause() {
+ // TODO: not implemented
+ }
+
+ @Override
+ public void resume() {
+ // TODO: not implemented
+ }
-
- /*public void printBestSolutions(int nrOfSolutions){
-
- algorithm.printBestSolutions(nrOfSolutions);
- }*/
-
-
-
-
}
Modified: trunk/src/dl-learner/org/dllearner/algorithms/refexamples/ExampleBasedROLearner.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/refexamples/ExampleBasedROLearner.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/algorithms/refexamples/ExampleBasedROLearner.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -33,6 +33,7 @@
import org.apache.log4j.Logger;
import org.dllearner.algorithms.refinement.RefinementOperator;
+import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasoningService;
import org.dllearner.core.Score;
@@ -455,8 +456,7 @@
String KBSyntax="KBSyntax:\n";
for(Description c : solutions) {
logger.info(show+": " + c.toString(baseURI,null) + " (length " + c.getLength() +", depth " + c.getDepth() + ")");
- // watch for String.replace Quick hack
- manchester+=show+": "+c.toManchesterSyntaxString(baseURI, new HashMap<String,String>()).replace("\"", "")+"\n";
+ manchester+=show+": "+c.toManchesterSyntaxString(baseURI, new HashMap<String,String>())+"\n";
KBSyntax+=show+": " + c.toKBSyntaxString()+"\n";
if(show>=5){break;} show++;
}
@@ -1059,43 +1059,34 @@
return candidatesStable.last().getConcept();
}
-
- public synchronized List<Description> getBestSolutions(int nrOfSolutions) {
- List<Description> best = new LinkedList<Description>();
+ public SortedSet<Description> getCurrentlyBestDescriptions() {
+ SortedSet<Description> best = new TreeSet<Description>();
int i=0;
+ int nrOfSolutions = 200;
for(ExampleBasedNode n : candidatesStable.descendingSet()) {
-
- best.add(n.getConcept());
- if(i==nrOfSolutions)
- return best;
+ best.add(n.getConcept());
+ if(i==nrOfSolutions)
+ return best;
i++;
}
return best;
}
-
- /**
- * returns the solutions, that have at least a certain quality
- * either accuracy = 100% full solutions
- * or accuracy > 100% - noise;
- * @return
- */
- public synchronized List<Description> getGoodSolutions() {
- List<Description> best = new LinkedList<Description>();
-
- for(ExampleBasedNode n : candidatesStable.descendingSet()) {
- if(n.getAccuracy(nrOfPositiveExamples, nrOfNegativeExamples)<(1-noise))
- return best;
- best.add(n.getConcept());
-
+ public SortedSet<EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions() {
+ int count = 0;
+ SortedSet<ExampleBasedNode> rev = candidatesStable.descendingSet();
+ SortedSet<EvaluatedDescription> cbd = new TreeSet<EvaluatedDescription>();
+ for(ExampleBasedNode eb : rev) {
+ cbd.add(new EvaluatedDescription(eb.getConcept(), getScore(eb.getConcept())));
+ // return a maximum of 200 elements (we need a maximum, because the
+ // candidate set can be very large)
+ if(count > 200)
+ return cbd;
+ count++;
}
- return best;
+ return cbd;
}
-
-
-
-
public void printBestSolutions(int nrOfSolutions, boolean showOrderedSolutions){
//QUALITY: could be optimized
if(!logger.isTraceEnabled())
@@ -1136,6 +1127,13 @@
return learningProblem.computeScore(getBestSolution());
}
+ private Score getScore(Description d) {
+ if(posOnly)
+ return posOnlyLearningProblem.computeScore(d);
+ else
+ return learningProblem.computeScore(d);
+ }
+
public ExampleBasedNode getStartNode() {
return startNode;
}
Modified: trunk/src/dl-learner/org/dllearner/algorithms/refinement/ROLearner.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/algorithms/refinement/ROLearner.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/algorithms/refinement/ROLearner.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -14,6 +14,7 @@
import org.apache.log4j.Level;
import org.apache.log4j.Logger;
+import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.LearningAlgorithm;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasoningService;
@@ -1033,8 +1034,13 @@
}
@Override
- public Description getBestSolution() {
+ public Description getCurrentlyBestDescription() {
return candidatesStable.last().getConcept();
+ }
+
+ @Override
+ public EvaluatedDescription getCurrentlyBestEvaluatedDescription() {
+ return new EvaluatedDescription(candidatesStable.last().getConcept(), getSolutionScore());
}
public void printBestSolutions(int nrOfSolutions){
@@ -1050,7 +1056,7 @@
}
@Override
- public synchronized List<Description> getBestSolutions(int nrOfSolutions) {
+ public synchronized List<Description> getCurrentlyBestDescriptions(int nrOfSolutions) {
List<Description> best = new LinkedList<Description>();
int i=0;
for(Node n : candidatesStable.descendingSet()) {
@@ -1065,9 +1071,9 @@
@Override
public Score getSolutionScore() {
if(posOnly)
- return posOnlyLearningProblem.computeScore(getBestSolution());
+ return posOnlyLearningProblem.computeScore(getCurrentlyBestEvaluatedDescription().getDescription());
else
- return learningProblem.computeScore(getBestSolution());
+ return learningProblem.computeScore(getCurrentlyBestEvaluatedDescription().getDescription());
}
Added: trunk/src/dl-learner/org/dllearner/core/EvaluatedDescription.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/core/EvaluatedDescription.java (rev 0)
+++ trunk/src/dl-learner/org/dllearner/core/EvaluatedDescription.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -0,0 +1,108 @@
+/**
+ * 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.core;
+
+import java.util.Set;
+
+import org.dllearner.core.owl.Description;
+import org.dllearner.core.owl.Individual;
+import org.dllearner.learningproblems.ScoreTwoValued;
+
+/**
+ * This represents a class description, which has been
+ * evaluated by the learning algorithm, i.e. it has been checked
+ * which examples it covers. It can be used as return value for
+ * learning algorithms to make it easier for applications to
+ * assess how good an offered class description is and how it
+ * classifies particular examples.
+ *
+ * @author Jens Lehmann
+ *
+ */
+public class EvaluatedDescription {
+
+ private Description description;
+ private Score score;
+
+ public EvaluatedDescription(Description description, Score score) {
+ this.description = description;
+ this.score = score;
+ }
+
+ public EvaluatedDescription(Description description, Set<Individual> posAsPos, Set<Individual> posAsNeg, Set<Individual> negAsPos, Set<Individual> negAsNeg) {
+ this.description = description;
+ // usually core methods should not depend on methods outside of the core package (except utilities)
+ // in this case, this is just a convenience constructor
+ score = new ScoreTwoValued(posAsPos, posAsNeg, negAsPos, negAsNeg);
+ }
+
+ public Description getDescription() {
+ return description;
+ }
+
+ public int getDescriptionLength() {
+ return description.getLength();
+ }
+
+ public int getDescriptionDepth() {
+ return description.getDepth();
+ }
+
+ /**
+ * @return
+ * @see org.dllearner.core.Score#getAccuracy()
+ */
+ public double getAccuracy() {
+ return score.getAccuracy();
+ }
+
+ /**
+ * @return
+ * @see org.dllearner.core.Score#getCoveredNegatives()
+ */
+ public Set<Individual> getCoveredNegatives() {
+ return score.getCoveredNegatives();
+ }
+
+ /**
+ * @return
+ * @see org.dllearner.core.Score#getCoveredPositives()
+ */
+ public Set<Individual> getCoveredPositives() {
+ return score.getCoveredPositives();
+ }
+
+ /**
+ * @return
+ * @see org.dllearner.core.Score#getNotCoveredNegatives()
+ */
+ public Set<Individual> getNotCoveredNegatives() {
+ return score.getNotCoveredNegatives();
+ }
+
+ /**
+ * @return
+ * @see org.dllearner.core.Score#getNotCoveredPositives()
+ */
+ public Set<Individual> getNotCoveredPositives() {
+ return score.getNotCoveredPositives();
+ }
+
+}
Modified: trunk/src/dl-learner/org/dllearner/core/LearningAlgorithm.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/core/LearningAlgorithm.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/core/LearningAlgorithm.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -1,5 +1,5 @@
/**
- * Copyright (C) 2007, Jens Lehmann
+ * Copyright (C) 2007-2008, Jens Lehmann
*
* This file is part of DL-Learner.
*
@@ -22,73 +22,188 @@
import java.util.Collection;
import java.util.LinkedList;
import java.util.List;
+import java.util.SortedSet;
+import java.util.TreeSet;
import org.dllearner.core.owl.Description;
+import org.dllearner.utilities.owl.ConceptTransformation;
/**
+ * Abstract superclass of all learning algorithm implementations.
+ * Includes support for anytime learning algorithms and resumable
+ * learning algorithms. Provides methods for filtering the best
+ * descriptions found by the algorithm. As results of the algorithm,
+ * you can either get only descriptions or evaluated descriptions.
+ * Evaluated descriptions have information about accuracy and
+ * example coverage associated with them. However, retrieving those
+ * may require addition reasoner queries, because the learning
+ * algorithms usually use but do not necessarily store this information.
+ *
* @author Jens Lehmann
*
*/
public abstract class LearningAlgorithm extends Component {
/**
- * Starts the algorithm.
- *
+ * Starts the algorithm. It runs until paused, stopped, or
+ * a termination criterion has been reached.
*/
public abstract void start();
-
/**
- * Stops the algorithm gracefully.
- *
+ * Pauses the algorithm (not all algorithms need to implement
+ * this operation).
*/
+ public void pause() { };
+
+ /**
+ * Resumes the algorithm (not all algorithms need to implement
+ * this operation). You can use this method to continue
+ * an algorithm run even after a termination criterion has been
+ * reached. It will run until paused, stopped, or terminated
+ * again.
+ */
+ public void resume() { };
+
+ /**
+ * Stops the algorithm gracefully. A stopped algorithm cannot be resumed anymore.
+ * Use this method for cleanup and freeing memory.
+ */
public abstract void stop();
-
+
/**
* Every algorithm must be able to return the score of the
* best solution found.
+ *
* @return Best score.
*/
+ @Deprecated
public abstract Score getSolutionScore();
/**
- * Returns the best solutions obtained so far.
- * @return Best solution.
+ * @see #getCurrentlyBestEvaluatedDescription()
*/
- public abstract Description getBestSolution();
+ public abstract Description getCurrentlyBestDescription();
+ /**
+ * @see #getCurrentlyBestEvaluatedDescriptions()
+ */
+ public SortedSet<Description> getCurrentlyBestDescriptions() {
+ TreeSet<Description> ds = new TreeSet<Description>();
+ ds.add(getCurrentlyBestDescription());
+ return ds;
+ }
+ /**
+ * @see #getCurrentlyBestEvaluatedDescriptions(int)
+ */
+ public synchronized List<Description> getCurrentlyBestDescriptions(int nrOfDescriptions) {
+ return getCurrentlyBestDescriptions(nrOfDescriptions, false);
+ }
/**
- * returns the best nrOfSolutions solutions
- * regardless of quality, just depends on input int
- * @param nrOfSolutions
- * @return List<Description>
+ * @see #getCurrentlyBestEvaluatedDescriptions(int,double,boolean)
*/
- public synchronized List<Description> getBestSolutions(int nrOfSolutions) {
- List<Description> single = new LinkedList<Description>();
- single.add(getBestSolution());
- return single;
+ public synchronized List<Description> getCurrentlyBestDescriptions(int nrOfDescriptions, boolean filterNonMinimalDescriptions) {
+ SortedSet<Description> currentlyBest = getCurrentlyBestDescriptions();
+ List<Description> returnList = new LinkedList<Description>();
+ int count = 0;
+ for(Description ed : currentlyBest) {
+ // return if we have sufficiently many descriptions
+ if(count >= nrOfDescriptions)
+ return returnList;
+
+ if(!filterNonMinimalDescriptions || ConceptTransformation.isDescriptionMinimal(ed))
+ returnList.add(ed);
+
+ count++;
+ }
+ return returnList;
+ }
+
+ /**
+ * Returns the best descriptions obtained so far.
+ * @return Best class description found so far.
+ */
+ public abstract EvaluatedDescription getCurrentlyBestEvaluatedDescription();
+
+ /**
+ * Returns a sorted set of the best descriptions found so far. We
+ * assume that they are ordered such that the best ones come in
+ * first.
+ * @return Best class descriptions found so far.
+ */
+ public SortedSet<EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions() {
+ TreeSet<EvaluatedDescription> ds = new TreeSet<EvaluatedDescription>();
+ ds.add(getCurrentlyBestEvaluatedDescription());
+ return ds;
}
/**
- * returns the solutions, that have at least a certain quality
- * either accuracy = 100%, i.e. full solutions
- * or accuracy > 100% - noise;
- * @return
+ * Returns a filtered list of currently best class descriptions.
+ *
+ * @param nrOfDescriptions Maximum number of restrictions. Use Integer.MAX_VALUE
+ * if you do not want this filter to be active.
+ *
+ * @param accuracyThreshold Minimum accuracy. All class descriptions with lower
+ * accuracy are disregarded. Specify a value between 0.0 and 1.0. Use 0.0 if
+ * you do not want this filter to be active.
+ *
+ * @param filterNonMinimalDescriptions If true, non-minimal descriptions are
+ * filtered, e.g. ALL r.TOP (being equivalent to TOP), male AND male (can be
+ * shortened to male). Currently, non-minimal descriptions are just skipped,
+ * i.e. they are completely omitted from the return list. Later, implementation
+ * might be changed to return shortened versions of those descriptions.
+ *
+ * @return A list of currently best class descriptions.
*/
- public synchronized List<Description> getGoodSolutions() {
- List<Description> single = new LinkedList<Description>();
- single.add(getBestSolution());
- return single;
+ public synchronized List<EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(int nrOfDescriptions, double accuracyThreshold, boolean filterNonMinimalDescriptions) {
+ SortedSet<EvaluatedDescription> currentlyBest = getCurrentlyBestEvaluatedDescriptions();
+ List<EvaluatedDescription> returnList = new LinkedList<EvaluatedDescription>();
+ int count = 0;
+ for(EvaluatedDescription ed : currentlyBest) {
+ // once we hit a description with a below threshold accuracy, we simply return
+ // because learning algorithms are advised to order descriptions by accuracy,
+ // so we won't find any concept with higher accuracy in the remaining list
+ if(ed.getAccuracy() < accuracyThreshold)
+ return returnList;
+
+ // return if we have sufficiently many descriptions
+ if(count >= nrOfDescriptions)
+ return returnList;
+
+ if(!filterNonMinimalDescriptions || ConceptTransformation.isDescriptionMinimal(ed.getDescription()))
+ returnList.add(ed);
+
+ count++;
+ }
+ return returnList;
}
+ /**
+ * Return the best currently found concepts up to some maximum
+ * count (no minimality filter used).
+ * @param nrOfDescriptions Maximum number of descriptions returned.
+ * @return Return value is getCurrentlyBestDescriptions(nrOfDescriptions, 0.0, false).
+ */
+ public synchronized List<EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(int nrOfDescriptions) {
+ return getCurrentlyBestEvaluatedDescriptions(nrOfDescriptions, 0.0, false);
+ }
/**
+ * Returns a fraction of class descriptions with sufficiently high accuracy.
+ * @param accuracyThreshold Only return solutions with this accuracy or higher.
+ * @return Return value is getCurrentlyBestDescriptions(Integer.MAX_VALUE, accuracyThreshold, false).
+ */
+ public synchronized List<EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(double accuracyThreshold) {
+ return getCurrentlyBestEvaluatedDescriptions(Integer.MAX_VALUE, accuracyThreshold, false);
+ }
+
+ /**
* Returns all learning problems supported by this component.
*/
public static Collection<Class<? extends LearningProblem>> supportedLearningProblems() {
return new LinkedList<Class<? extends LearningProblem>>();
}
-
+
}
Modified: trunk/src/dl-learner/org/dllearner/core/Score.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/core/Score.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/core/Score.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -1,3 +1,23 @@
+/**
+ * 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.core;
import java.util.Set;
@@ -4,9 +24,26 @@
import org.dllearner.core.owl.Individual;
+/**
+ * The score class is used to store how well a class description did
+ * on a learning problem.
+ *
+ * @author Jens Lehmann
+ *
+ */
public abstract class Score {
+
+ // accuracy
+ public abstract double getAccuracy();
+
+ // example coverage
+ public abstract Set<Individual> getCoveredPositives();
+ public abstract Set<Individual> getCoveredNegatives();
+ public abstract Set<Individual> getNotCoveredPositives();
+ public abstract Set<Individual> getNotCoveredNegatives();
+
+ // older methods (not frequently used anymore)
public abstract double getScore();
-
/**
* The score of a concept depends on how good it classifies the
* examples of a learning problem and the length of the concept
@@ -20,9 +57,4 @@
*/
public abstract Score getModifiedLengthScore(int newLength);
- public abstract Set<Individual> getCoveredPositives();
- public abstract Set<Individual> getCoveredNegatives();
- public abstract Set<Individual> getNotCoveredPositives();
-
- // public abstract int getNrOfMiss
}
Modified: trunk/src/dl-learner/org/dllearner/examples/KRKModular.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/examples/KRKModular.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/examples/KRKModular.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -284,7 +284,7 @@
//System.out.println("best"+la.getBestSolution());
}catch (Exception e) {e.printStackTrace();}
- return la.getBestSolution();
+ return la.getCurrentlyBestDescription();
}
static KB getKB(SortedSet<Integer> lines){
Modified: trunk/src/dl-learner/org/dllearner/gui/MiniGUI.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/gui/MiniGUI.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/gui/MiniGUI.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -198,7 +198,7 @@
// wait for a solution (note that not all learning problems have a
// solution (100% accuracy), so one usually has to run the algorithm in its own
// thread, such that it can be aborted after some time
- Description solution = la.getBestSolution();
+ Description solution = la.getCurrentlyBestDescription();
solutionDisplay.setText(solution.toString());
}
}
Modified: trunk/src/dl-learner/org/dllearner/gui/RunPanel.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/gui/RunPanel.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/gui/RunPanel.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -172,9 +172,9 @@
infoArea.setText("");
// best solutions
- if (config.getLearningAlgorithm().getBestSolutions(5) != null) {
+ if (config.getLearningAlgorithm().getCurrentlyBestEvaluatedDescriptions(5) != null) {
infoArea.append("Best solutions: \n\n"
- + listToString(config.getLearningAlgorithm().getBestSolutions(10)) + "\n");
+ + listToString(config.getLearningAlgorithm().getCurrentlyBestEvaluatedDescriptions(10)) + "\n");
}
// solution score
// if (config.getLearningAlgorithm().getSolutionScore() != null)
@@ -257,7 +257,7 @@
if (millis > 0)
time += millis + "ms ";
if (false)
- time += mikros + "\xB5s ";
+ time += mikros + "�s ";
if (false)
time += nanos + "ns ";
return time;
Modified: trunk/src/dl-learner/org/dllearner/learningproblems/ScoreThreeValued.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/learningproblems/ScoreThreeValued.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/learningproblems/ScoreThreeValued.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -233,6 +233,22 @@
@Override
public Score getModifiedLengthScore(int newLength) {
return new ScoreThreeValued(newLength, accuracyPenalty, errorPenalty, penaliseNeutralExamples, percentPerLengthUnit, posClassified, neutClassified, negClassified, posExamples, neutExamples, negExamples);
+ }
+
+ /* (non-Javadoc)
+ * @see org.dllearner.core.Score#getAccuracy()
+ */
+ @Override
+ public double getAccuracy() {
+ return accuracy;
+ }
+
+ /* (non-Javadoc)
+ * @see org.dllearner.core.Score#getNotCoveredNegatives()
+ */
+ @Override
+ public Set<Individual> getNotCoveredNegatives() {
+ return negAsNeg;
}
}
Modified: trunk/src/dl-learner/org/dllearner/learningproblems/ScoreTwoValued.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/learningproblems/ScoreTwoValued.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/learningproblems/ScoreTwoValued.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -1,3 +1,23 @@
+/**
+ * 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.learningproblems;
import java.util.Set;
@@ -6,10 +26,15 @@
import org.dllearner.core.owl.Individual;
/**
+ * Calculates accuracy and score (with respect to some length penalty) of
+ * a class description.
*
- * TODO: accuracy-Berechnung (positive+negative Beispiele muessen dafuer bekannt sein)
+ * TODO: In fact, a score value influencing a learning algorithm
+ * should not be calculated here, but rather in a separate heuristic
+ * as there are many methods to calculate such a value. This class
+ * should only be used for computing example coverage, accuracy etc.
*
- * @author jl
+ * @author Jens Lehmann
*
*/
public class ScoreTwoValued extends Score {
@@ -19,11 +44,15 @@
private Set<Individual> negAsPos;
private Set<Individual> negAsNeg;
private double score;
- private double classificationScore;
+ private double accuracy;
private int nrOfExamples;
private int conceptLength;
private double percentPerLengthUnit;
+ public ScoreTwoValued(Set<Individual> posAsPos, Set<Individual> posAsNeg, Set<Individual> negAsPos, Set<Individual> negAsNeg) {
+ this(0,0,posAsPos,posAsNeg,negAsPos,posAsPos);
+ }
+
public ScoreTwoValued(int conceptLength, double percentPerLengthUnit, Set<Individual> posAsPos, Set<Individual> posAsNeg, Set<Individual> negAsPos, Set<Individual> negAsNeg) {
this.conceptLength = conceptLength;
this.percentPerLengthUnit = percentPerLengthUnit;
@@ -36,15 +65,22 @@
}
private void computeScore() {
- // - Anzahl falscher Klassifikationen
- classificationScore = - posAsNeg.size() - negAsPos.size();
- // Anteil falscher Klassifikationen (Zahl zwischen -1 und 0)
- classificationScore = classificationScore / (double) nrOfExamples;
- // Berücksichtigung des Längenfaktors
- score = classificationScore - percentPerLengthUnit * conceptLength;
+ // compute accuracy
+ accuracy = posAsPos.size() + negAsNeg.size();
+ accuracy = accuracy / (double) nrOfExamples;
+ // compute score
+ score = accuracy - 1 - percentPerLengthUnit * conceptLength;
}
@Override
+ public double getAccuracy() {
+ return accuracy;
+ }
+
+ /**
+ * score = accuracy - 1 - length * length penalty
+ */
+ @Override
public double getScore() {
return score;
}
@@ -53,7 +89,7 @@
public String toString() {
String str = "";
str += "score: " + score + "\n";
- str += "accuracy: " + (1 + classificationScore) + "\n";
+ str += "accuracy: " + accuracy + "\n";
str += "posAsPos (" + posAsPos.size() + "): " + posAsPos + "\n";
str += "positive examples classified as negative (" + posAsNeg.size() + "): " + posAsNeg + "\n";
str += "negative examples classified as positive (" + negAsPos.size() + "): " + negAsPos + "\n";
@@ -74,16 +110,15 @@
public Set<Individual> getNotCoveredPositives() {
return posAsNeg;
}
-
- /*
+
@Override
- public double getModifiedLengthScore(int newLength) {
- return classificationScore - Config.percentPerLengthUnit * newLength;
- }
- */
+ public Set<Individual> getNotCoveredNegatives() {
+ return negAsNeg;
+ }
@Override
public Score getModifiedLengthScore(int newLength) {
return new ScoreTwoValued(newLength, percentPerLengthUnit, posAsPos, posAsNeg, negAsPos, negAsNeg);
- }
+ }
+
}
Modified: trunk/src/dl-learner/org/dllearner/scripts/CrossValidation.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/CrossValidation.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/scripts/CrossValidation.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -222,7 +222,7 @@
long algorithmDuration = System.nanoTime() - algorithmStartTime;
runtime.addNumber(algorithmDuration/(double)1000000000);
- Description concept = la.getBestSolution();
+ Description concept = la.getCurrentlyBestDescription();
ReasoningService rs = start.getReasoningService();
Set<Individual> tmp = rs.instanceCheck(concept, testSetsPos.get(currFold));
Modified: trunk/src/dl-learner/org/dllearner/scripts/SKOS7030.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/SKOS7030.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/scripts/SKOS7030.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -89,7 +89,7 @@
s.makeExamples(prim, percentOfSKOSSet, negfactor, sparqlResultSize);
- List<Description> conceptresults = s.learn();
+ SortedSet<Description> conceptresults = s.learn();
logger.debug("found nr of concepts: "+conceptresults.size());
System.out.println(conceptresults);
@@ -249,7 +249,7 @@
logger.debug(fullPosSetWithoutPosExamples);
}
- public List<Description> learn(){
+ public SortedSet<Description> learn(){
SortedSet<String> instances = new TreeSet<String>();
instances.addAll(this.posExamples);
@@ -330,7 +330,7 @@
//Statistics.addTimeLearning(sc.getTime());
- return la.getGoodSolutions();
+ return la.getCurrentlyBestDescriptions();
}catch (Exception e) {e.printStackTrace();}
return null;
Modified: trunk/src/dl-learner/org/dllearner/scripts/TestValidation.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/TestValidation.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/scripts/TestValidation.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -57,7 +57,7 @@
Start start = new Start(new File(filenameTrain));
start.start(false);
- Description solution = start.getLearningAlgorithm().getBestSolution();
+ Description solution = start.getLearningAlgorithm().getCurrentlyBestDescription();
logger.setLevel(Level.WARN);
Modified: trunk/src/dl-learner/org/dllearner/server/DLLearnerWS.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/server/DLLearnerWS.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/server/DLLearnerWS.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -308,7 +308,7 @@
public String learn(int id, String format) throws ClientNotKnownException {
ClientState state = getState(id);
state.getLearningAlgorithm().start();
- Description solution = state.getLearningAlgorithm().getBestSolution();
+ Description solution = state.getLearningAlgorithm().getCurrentlyBestDescription();
if(format.equals("manchester"))
return solution.toManchesterSyntaxString(state.getReasoningService().getBaseURI(), new HashMap<String,String>());
else if(format.equals("kb"))
@@ -342,13 +342,13 @@
@WebMethod
public String getCurrentlyBestConcept(int id) throws ClientNotKnownException {
ClientState state = getState(id);
- return state.getLearningAlgorithm().getBestSolution().toString();
+ return state.getLearningAlgorithm().getCurrentlyBestEvaluatedDescription().toString();
}
@WebMethod
public String[] getCurrentlyBestConcepts(int id, int nrOfConcepts) throws ClientNotKnownException {
ClientState state = getState(id);
- List<Description> bestConcepts = state.getLearningAlgorithm().getBestSolutions(nrOfConcepts);
+ List<Description> bestConcepts = state.getLearningAlgorithm().getCurrentlyBestDescriptions(nrOfConcepts);
List<String> conc=new LinkedList<String>();
Iterator<Description> iter=bestConcepts.iterator();
while (iter.hasNext())
@@ -612,7 +612,7 @@
@WebMethod
public int[] getConceptDepth(int id, int nrOfConcepts) throws ClientNotKnownException {
ClientState state = getState(id);
- List<Description> bestConcepts = state.getLearningAlgorithm().getBestSolutions(nrOfConcepts);
+ List<Description> bestConcepts = state.getLearningAlgorithm().getCurrentlyBestDescriptions(nrOfConcepts);
Iterator<Description> iter=bestConcepts.iterator();
int[] length=new int[bestConcepts.size()];
int i=0;
@@ -626,7 +626,7 @@
@WebMethod
public int[] getConceptArity(int id, int nrOfConcepts) throws ClientNotKnownException {
ClientState state = getState(id);
- List<Description> bestConcepts = state.getLearningAlgorithm().getBestSolutions(nrOfConcepts);
+ List<Description> bestConcepts = state.getLearningAlgorithm().getCurrentlyBestDescriptions(nrOfConcepts);
Iterator<Description> iter=bestConcepts.iterator();
int[] arity=new int[bestConcepts.size()];
int i=0;
Modified: trunk/src/dl-learner/org/dllearner/test/ComponentTest.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/test/ComponentTest.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/test/ComponentTest.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -97,7 +97,7 @@
// start the algorithm and print the best concept found
la.start();
- System.out.println(la.getBestSolution());
+ System.out.println(la.getCurrentlyBestEvaluatedDescription());
}
}
Modified: trunk/src/dl-learner/org/dllearner/tools/ore/LearningPanelDescriptor.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/tools/ore/LearningPanelDescriptor.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/tools/ore/LearningPanelDescriptor.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -69,7 +69,7 @@
la = getWizardModel().getOre().start();//started endlosen Algorithmus
- publish(la.getBestSolutions(10));
+ publish(la.getCurrentlyBestDescriptions(10));
List<Description> result = getWizardModel().getOre().getLearningResults(100);
Modified: trunk/src/dl-learner/org/dllearner/tools/ore/ORE.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/tools/ore/ORE.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/tools/ore/ORE.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -177,15 +177,15 @@
}
public Description getLearningResult(){
- return la.getBestSolution();
+ return la.getCurrentlyBestDescription();
}
- public List<Description> getSolutions(){
- return la.getGoodSolutions();
- }
+// public List<Description> getSolutions(){
+// return la.getCurrentlyBestDescriptions();
+// }
public List<Description> getLearningResults(int anzahl){
- return la.getBestSolutions(anzahl);
+ return la.getCurrentlyBestDescriptions(anzahl);
}
/**
Modified: trunk/src/dl-learner/org/dllearner/tools/protege/DLLearnerModel.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/tools/protege/DLLearnerModel.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/tools/protege/DLLearnerModel.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -224,9 +224,9 @@
*/
private void addToListModel()
{
- for(int j = 0;j<la.getBestSolutions(anzahl).size();j++)
+ for(int j = 0;j<la.getCurrentlyBestEvaluatedDescriptions(anzahl).size();j++)
{
- suggestModel.add(j,la.getBestSolutions(anzahl).get(j));
+ suggestModel.add(j,la.getCurrentlyBestEvaluatedDescriptions(anzahl).get(j));
}
}
@@ -352,7 +352,7 @@
error = "Learning succesful";
// start the algorithm and print the best concept found
la.start();
- description = new Description[la.getBestSolutions(anzahl).size()];
+ description = new Description[la.getCurrentlyBestEvaluatedDescriptions(anzahl).size()];
addToListModel();
view.renderErrorMessage(error);
view.getRunButton().setEnabled(true);
Modified: trunk/src/dl-learner/org/dllearner/utilities/owl/ConceptTransformation.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/utilities/owl/ConceptTransformation.java 2008-06-27 13:44:33 UTC (rev 985)
+++ trunk/src/dl-learner/org/dllearner/utilities/owl/ConceptTransformation.java 2008-06-27 14:28:48 UTC (rev 986)
@@ -1,3 +1,22 @@
+/**
+ * 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.utilities.owl;
import java.util.Collections;
@@ -21,8 +40,11 @@
import org.dllearner.core.owl.ObjectQuantorRestriction;
import org.dllearner.core.owl.Thing;
-// ev. kann man diese Klasse später in ein anderes Paket ziehen, da sie nicht direkt mit
-// refinement zu tun hat
+/**
+ * Concept transformation and concept checking methods.
+ *
+ * @author Jens Lehmann
+ */
public class ConceptTransformation {
public static long cleaningTimeNs = 0;
@@ -386,4 +408,39 @@
return concept;
}
+ /**
+ * Method to determine, whether a class description is minimal,
+ * e.g. \forall r.\top (\equiv \top) or male \sqcup male are not
+ * minimal. This method performs heuristic sanity checks (it will
+ * not try to find semantically equivalent shorter descriptions).
+ * @param description Input description.
+ * @return True if a superfluous construct has been found.
+ */
+ public static boolean isDescriptionMinimal(Description description) {
+ ConceptComparator cc = new ConceptComparator();
+ int length = description.getLength();
+ int length2 = ConceptTransformation.getShortConcept(description, cc).getLength();
+ if(length2 < length)
+ return false;
+ if(ConceptTransformation.findEquivalences(description))
+ return false;
+ return true;
+ }
+
+ private static boolean findEquivalences(Description description) {
+ // \exists r.\bot \equiv \bot
+ if(description instanceof ObjectSomeRestriction && description.getChild(0) instanceof Nothing)
+ return true;
+ // \forall r.\top \equiv \top
+ if(description instanceof ObjectAllRestriction && description.getChild(0) instanceof Thing)
+ return true;
+ // check children
+ for(Description child : description.getChildren()) {
+ if(findEquivalences(child))
+ return true;
+ }
+ // false if none of the checks was successful
+ return false;
+ }
+
}
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