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[DL-Learner SVN] SF.net SVN: dl-learner:[3063] trunk
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From: <jen...@us...> - 2011-08-17 19:24:02
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Revision: 3063
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=3063&view=rev
Author: jenslehmann
Date: 2011-08-17 18:38:28 +0000 (Wed, 17 Aug 2011)
Log Message:
-----------
implemented new simple negative example finder for SPARQL and integrated it in enrichment script
Modified Paths:
--------------
trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java
trunk/components-core/src/main/java/org/dllearner/kb/sparql/SPARQLTasks.java
trunk/interfaces/src/main/java/org/dllearner/cli/Enrichment.java
Added Paths:
-----------
trunk/components-core/src/main/java/org/dllearner/utilities/examples/AutomaticNegativeExampleFinderSPARQL2.java
Modified: trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java 2011-08-17 14:34:36 UTC (rev 3062)
+++ trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java 2011-08-17 18:38:28 UTC (rev 3063)
@@ -100,7 +100,7 @@
"org.dllearner.kb.KBFile",
"org.dllearner.kb.sparql.SparqlKnowledgeSource",
"org.dllearner.kb.OWLAPIOntology",
- "org.dllearner.kb.SparqlEndpointKS",
+// "org.dllearner.kb.SparqlEndpointKS",
//reasoners
"org.dllearner.reasoning.OWLAPIReasoner",
"org.dllearner.reasoning.fuzzydll.FuzzyOWLAPIReasoner", // added by Josue
Modified: trunk/components-core/src/main/java/org/dllearner/kb/sparql/SPARQLTasks.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/kb/sparql/SPARQLTasks.java 2011-08-17 14:34:36 UTC (rev 3062)
+++ trunk/components-core/src/main/java/org/dllearner/kb/sparql/SPARQLTasks.java 2011-08-17 18:38:28 UTC (rev 3063)
@@ -1,5 +1,5 @@
/**
- * Copyright (C) 2007-2008, Jens Lehmann
+ * Copyright (C) 2007-2011, Jens Lehmann
*
* This file is part of DL-Learner.
*
@@ -38,12 +38,14 @@
import com.hp.hpl.jena.query.ResultSetFactory;
import com.hp.hpl.jena.query.ResultSetFormatter;
import com.hp.hpl.jena.query.ResultSetRewindable;
-import com.hp.hpl.jena.sparql.core.ResultBinding;
/**
- * @author Sebastian Hellmann Convenience class for SPARQL queries initialized
+ * Convenience class for SPARQL queries initialized
* with a SparqlEndpoint. A Cache can also be used to further improve
* query time. Some methods allow basic reasoning
+ *
+ * @author Sebastian Hellmann
+ * @author Jens Lehmann
*/
public class SPARQLTasks {
@@ -93,6 +95,16 @@
// TODO check for quotes in uris
return getRecursiveSuperOrSubClasses(classURI, maxDepth, false);
}
+
+ public SortedSet<String> getParallelClasses(String classURI, int limit) {
+ String query = "SELECT ?sub WHERE { <" + classURI + "> <http://www.w3.org/2000/01/rdf-schema#subClassOf> ?super .";
+ query += "?sub <http://www.w3.org/2000/01/rdf-schema#subClassOf> ?super .";
+ query += "FILTER( ?sub != <" + classURI + ">) . } LIMIT " + limit;
+ return queryAsSet(query, "?sub");
+// SparqlQuery sq = new SparqlQuery(query, sparqlEndpoint);
+// ResultSet rs = sq.send();
+
+ }
/**
* This is the underlying function to get Super and SubClasses.
Added: trunk/components-core/src/main/java/org/dllearner/utilities/examples/AutomaticNegativeExampleFinderSPARQL2.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/utilities/examples/AutomaticNegativeExampleFinderSPARQL2.java (rev 0)
+++ trunk/components-core/src/main/java/org/dllearner/utilities/examples/AutomaticNegativeExampleFinderSPARQL2.java 2011-08-17 18:38:28 UTC (rev 3063)
@@ -0,0 +1,85 @@
+/**
+ * Copyright (C) 2007-2011, 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.examples;
+
+import java.util.Set;
+import java.util.SortedSet;
+import java.util.TreeSet;
+
+import org.dllearner.core.owl.NamedClass;
+import org.dllearner.kb.SparqlEndpointKS;
+import org.dllearner.kb.sparql.SPARQLTasks;
+import org.dllearner.kb.sparql.SparqlEndpoint;
+import org.dllearner.reasoning.SPARQLReasoner;
+import org.dllearner.utilities.datastructures.Datastructures;
+
+/**
+ *
+ * Utility class for automatically retrieving negative examples from a
+ * SPARQL endpoint given a set of positive examples.
+ *
+ * @author Jens Lehmann
+ * @author Sebastian Hellmann
+ *
+ */
+public class AutomaticNegativeExampleFinderSPARQL2 {
+
+ private SparqlEndpoint se;
+
+ // for re-using existing queries
+ private SPARQLReasoner sr;
+ private SPARQLTasks st;
+
+ public AutomaticNegativeExampleFinderSPARQL2(SparqlEndpoint se) {
+ this.se = se;
+ SparqlEndpointKS ks = new SparqlEndpointKS(se);
+ sr = new SPARQLReasoner(ks);
+ st = new SPARQLTasks(se);
+ }
+
+ /**
+ * Get negative examples when learning the description of a class, i.e.
+ * all positives are from some known class.
+ *
+ * Currently, the method implementation is preliminary and does not allow
+ * to configure internals.
+ *
+ * @param classURI The known class of all positive examples.
+ * @param positiveExamples The existing positive examples.
+ */
+ public SortedSet<String> getNegativeExamples(String classURI, SortedSet<String> positiveExamples) {
+ // get some individuals from parallel classes (we perform one query per class to avoid
+ // only getting individuals from a single class)
+ Set<String> parallelClasses = st.getParallelClasses(classURI, 5); // TODO: limit could be configurable
+ SortedSet<String> negEx = new TreeSet<String>();
+ for(String parallelClass : parallelClasses) {
+ Set<String> inds = Datastructures.individualSetToStringSet(sr.getIndividuals(new NamedClass(parallelClass), 10));
+ negEx.addAll(inds);
+ if(negEx.size()>100) {
+ return negEx;
+ }
+ }
+ // add some random instances
+ String query = "SELECT ?inst { ?inst <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> ?x } LIMIT 20";
+ negEx.addAll(st.queryAsSet(query, "?inst"));
+ return negEx;
+ }
+
+}
Modified: trunk/interfaces/src/main/java/org/dllearner/cli/Enrichment.java
===================================================================
--- trunk/interfaces/src/main/java/org/dllearner/cli/Enrichment.java 2011-08-17 14:34:36 UTC (rev 3062)
+++ trunk/interfaces/src/main/java/org/dllearner/cli/Enrichment.java 2011-08-17 18:38:28 UTC (rev 3063)
@@ -36,6 +36,7 @@
import java.util.LinkedList;
import java.util.List;
import java.util.Map.Entry;
+import java.util.Set;
import java.util.SortedSet;
import java.util.TreeSet;
@@ -99,8 +100,10 @@
import org.dllearner.utilities.EnrichmentVocabulary;
import org.dllearner.utilities.Helper;
import org.dllearner.utilities.datastructures.Datastructures;
+import org.dllearner.utilities.datastructures.SetManipulation;
import org.dllearner.utilities.datastructures.SortedSetTuple;
import org.dllearner.utilities.examples.AutomaticNegativeExampleFinderSPARQL;
+import org.dllearner.utilities.examples.AutomaticNegativeExampleFinderSPARQL2;
import org.semanticweb.owlapi.apibinding.OWLManager;
import org.semanticweb.owlapi.io.SystemOutDocumentTarget;
import org.semanticweb.owlapi.model.IRI;
@@ -185,7 +188,6 @@
classAlgorithms.add(CELOE.class);
}
- @SuppressWarnings("unchecked")
public void start() throws ComponentInitException, IllegalArgumentException, SecurityException, InstantiationException, IllegalAccessException, InvocationTargetException, NoSuchMethodException, LearningProblemUnsupportedException, MalformedURLException {
// sanity check that endpoint/graph returns at least one triple
@@ -210,15 +212,18 @@
st.getAllObjectProperties();
} else {
if(resource instanceof ObjectProperty) {
+ System.out.println(resource + " appears to be an object property. Running appropriate algorithms.");
for (Class<? extends AxiomLearningAlgorithm> algorithmClass : objectPropertyAlgorithms) {
applyLearningAlgorithm(algorithmClass, ks);
}
} else if(resource instanceof DatatypeProperty) {
+ System.out.println(resource + " appears to be a data property. Running appropriate algorithms.");
for (Class<? extends AxiomLearningAlgorithm> algorithmClass : dataPropertyAlgorithms) {
applyLearningAlgorithm(algorithmClass, ks);
}
} else if(resource instanceof NamedClass) {
+ System.out.println(resource + " appears to be a class. Running appropriate algorithms.");
for (Class<? extends LearningAlgorithm> algorithmClass : classAlgorithms) {
if(algorithmClass == CELOE.class) {
applyCELOE(ks, false);
@@ -234,24 +239,31 @@
}
private List<EvaluatedAxiom> applyCELOE(SparqlEndpointKS ks, boolean equivalence) throws ComponentInitException, LearningProblemUnsupportedException, MalformedURLException {
- SPARQLTasks st = new SPARQLTasks(se);
+// SPARQLTasks st = new SPARQLTasks(se);
// get instances of class as positive examples
SPARQLReasoner sr = new SPARQLReasoner(ks);
- SortedSet<Individual> posExamples = sr.getIndividuals((NamedClass)resource, 50);
+ SortedSet<Individual> posExamples = sr.getIndividuals((NamedClass)resource, 20);
SortedSet<String> posExStr = Helper.getStringSet(posExamples);
// get negative examples via various strategies
- AutomaticNegativeExampleFinderSPARQL finder = new AutomaticNegativeExampleFinderSPARQL(posExStr, st, null);
- finder.makeNegativeExamplesFromNearbyClasses(posExStr, 50);
- finder.makeNegativeExamplesFromParallelClasses(posExStr, 50);
- finder.makeNegativeExamplesFromRelatedInstances(posExStr, "http://dbpedia.org/resource/");
- finder.makeNegativeExamplesFromSuperClasses(resource.getName(), 50);
+// AutomaticNegativeExampleFinderSPARQL finder = new AutomaticNegativeExampleFinderSPARQL(posExStr, st, null);
+// finder.makeNegativeExamplesFromNearbyClasses(posExStr, 50);
+// finder.makeNegativeExamplesFromParallelClasses(posExStr, 50);
+// finder.makeNegativeExamplesFromRelatedInstances(posExStr, "http://dbpedia.org/resource/");
+// finder.makeNegativeExamplesFromSuperClasses(resource.getName(), 50);
// finder.makeNegativeExamplesFromRandomInstances();
- SortedSet<String> negExStr = finder.getNegativeExamples(50, false);
+// SortedSet<String> negExStr = finder.getNegativeExamples(50, false);
+ // use own implementation of negative example finder
+ System.out.print("finding negatives ... ");
+ AutomaticNegativeExampleFinderSPARQL2 finder = new AutomaticNegativeExampleFinderSPARQL2(ks.getEndpoint());
+ SortedSet<String> negExStr = finder.getNegativeExamples(resource.getName(), posExStr);
+ negExStr = SetManipulation.fuzzyShrink(negExStr, 20);
SortedSet<Individual> negExamples = Helper.getIndividualSet(negExStr);
SortedSetTuple<Individual> examples = new SortedSetTuple<Individual>(posExamples, negExamples);
+ System.out.println("done (" + negExStr.size()+ ")");
+
ComponentManager cm = ComponentManager.getInstance();
SparqlKnowledgeSource ks2 = cm.knowledgeSource(SparqlKnowledgeSource.class);
@@ -263,7 +275,9 @@
ks2.getConfigurator().setRecursionDepth(1);
ks2.getConfigurator().setCloseAfterRecursion(true);
// ks2.getConfigurator().setSaveExtractedFragment(true);
+ System.out.println("getting fragment ... ");
ks2.init();
+ System.out.println("done");
AbstractReasonerComponent rc = cm.reasoner(FastInstanceChecker.class, ks2);
rc.init();
@@ -276,15 +290,17 @@
lp.getConfigurator().setType("equivalence");
lp.getConfigurator().setAccuracyMethod("fmeasure");
lp.getConfigurator().setUseApproximations(false);
+ lp.getConfigurator().setMaxExecutionTimeInSeconds(10);
lp.init();
-
CELOE la = cm.learningAlgorithm(CELOE.class, lp, rc);
CELOEConfigurator cc = la.getConfigurator();
cc.setMaxExecutionTimeInSeconds(100);
cc.setNoisePercentage(20);
la.init();
+ System.out.print("running CELOE ... ");
la.start();
+ System.out.println("done");
// convert the result to axioms (to make it compatible with the other algorithms)
TreeSet<? extends EvaluatedDescription> learnedDescriptions = la.getCurrentlyBestEvaluatedDescriptions();
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