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[DL-Learner SVN] SF.net SVN: dl-learner: [810] trunk/src/dl-learner/org/dllearner
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From: <ku...@us...> - 2008-04-22 15:23:48
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Revision: 810
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=810&view=rev
Author: kurzum
Date: 2008-04-22 08:23:38 -0700 (Tue, 22 Apr 2008)
Log Message:
-----------
moved some classes to new package scripts, because, they are neither utitlity classes nor test classes, but scripts.
Added Paths:
-----------
trunk/src/dl-learner/org/dllearner/scripts/
trunk/src/dl-learner/org/dllearner/scripts/CloseOntology.java
trunk/src/dl-learner/org/dllearner/scripts/CrossValidation.java
trunk/src/dl-learner/org/dllearner/scripts/NT2RDF.java
trunk/src/dl-learner/org/dllearner/scripts/SPARQLPreparation.java
Removed Paths:
-------------
trunk/src/dl-learner/org/dllearner/test/SPARQLPreparation.java
trunk/src/dl-learner/org/dllearner/utilities/CloseOntology.java
trunk/src/dl-learner/org/dllearner/utilities/CrossValidation.java
trunk/src/dl-learner/org/dllearner/utilities/NT2RDF.java
Copied: trunk/src/dl-learner/org/dllearner/scripts/CloseOntology.java (from rev 808, trunk/src/dl-learner/org/dllearner/utilities/CloseOntology.java)
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/CloseOntology.java (rev 0)
+++ trunk/src/dl-learner/org/dllearner/scripts/CloseOntology.java 2008-04-22 15:23:38 UTC (rev 810)
@@ -0,0 +1,66 @@
+package org.dllearner.scripts;
+
+import java.io.File;
+import java.net.URI;
+import java.util.HashSet;
+import java.util.Set;
+
+import org.dllearner.core.KnowledgeSource;
+import org.dllearner.kb.OWLFile;
+import org.dllearner.reasoning.OWLAPIReasoner;
+import org.dllearner.utilities.OntologyCloserOWLAPI;
+
+/**
+ * Script for closing an ontology OWLAPI produces extensive filesizes, when
+ * exporting output file ist named like input file, but recieves a
+ * "_closedConcise" at the end.
+ *
+ * Counts all roles of individuals and adds an Intersection (Concise) of
+ * ExactCardinalityRestriction to the ABox
+ *
+ */
+public class CloseOntology {
+
+ /**
+ * @param argument0
+ * simply the path to the owl ontology "examples/test.owl"
+ */
+ public static void main(String[] args) {
+ String ontopath="";
+ //ontopath="examples/carcinogenesis/carcinogenesis.owl";
+ // inputURI
+ //ontopath = args[0];
+ File file = new File(ontopath);
+ URI inputURI = file.toURI();
+
+ // outputURI
+ String ending = ontopath.substring(ontopath.lastIndexOf(".") + 1);
+ ontopath = ontopath.replace("." + ending, "_closedConcise." + ending);
+ file = new File(ontopath);
+ URI outputURI = file.toURI();
+
+ try {
+ // initializing reasoner
+ OWLFile owlFile = new OWLFile();
+ owlFile.setURL(inputURI.toURL());
+ Set<KnowledgeSource> ks = new HashSet<KnowledgeSource>();
+ ks.add(owlFile);
+ OWLAPIReasoner owlapireasoner = new OWLAPIReasoner(ks);
+ owlapireasoner.init();
+
+ // close
+ OntologyCloserOWLAPI oc = new OntologyCloserOWLAPI(owlapireasoner);
+ oc.testForTransitiveProperties(true);
+ System.out.println("Attempting to close");
+ oc.applyNumberRestrictionsConcise();
+ System.out.println("Finished, preparing output");
+
+ // save
+ oc.writeOWLFile(outputURI);
+
+ } catch (Exception e) {
+ e.printStackTrace();
+ }
+ }
+
+}
Copied: trunk/src/dl-learner/org/dllearner/scripts/CrossValidation.java (from rev 808, trunk/src/dl-learner/org/dllearner/utilities/CrossValidation.java)
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/CrossValidation.java (rev 0)
+++ trunk/src/dl-learner/org/dllearner/scripts/CrossValidation.java 2008-04-22 15:23:38 UTC (rev 810)
@@ -0,0 +1,318 @@
+/**
+ * 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.scripts;
+
+import java.io.File;
+import java.text.DecimalFormat;
+import java.util.Collections;
+import java.util.HashSet;
+import java.util.LinkedList;
+import java.util.List;
+import java.util.Random;
+import java.util.Set;
+
+import org.apache.log4j.ConsoleAppender;
+import org.apache.log4j.Level;
+import org.apache.log4j.Logger;
+import org.apache.log4j.SimpleLayout;
+import org.dllearner.cli.Start;
+import org.dllearner.core.ComponentInitException;
+import org.dllearner.core.ComponentManager;
+import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.LearningProblem;
+import org.dllearner.core.ReasoningService;
+import org.dllearner.core.owl.Description;
+import org.dllearner.core.owl.Individual;
+import org.dllearner.learningproblems.PosNegLP;
+import org.dllearner.learningproblems.PosOnlyLP;
+import org.dllearner.utilities.Datastructures;
+import org.dllearner.utilities.Helper;
+import org.dllearner.utilities.Stat;
+
+/**
+ * Performs cross validation for the given problem. Supports
+ * k-fold cross-validation and leave-one-out cross-validation.
+ *
+ * @author Jens Lehmann
+ *
+ */
+public class CrossValidation {
+
+ private static Logger logger = Logger.getRootLogger();
+
+ public static void main(String[] args) {
+ File file = new File(args[0]);
+
+ boolean leaveOneOut = false;
+ int folds = 10;
+
+ // use second argument as number of folds; if not specified
+ // leave one out cross validation is used
+ if(args.length > 1)
+ folds = Integer.parseInt(args[1]);
+ else
+ leaveOneOut = true;
+
+ if(folds < 2) {
+ System.out.println("At least 2 fold needed.");
+ System.exit(0);
+ }
+
+ // create logger (a simple logger which outputs
+ // its messages to the console)
+ SimpleLayout layout = new SimpleLayout();
+ ConsoleAppender consoleAppender = new ConsoleAppender(layout);
+ logger.removeAllAppenders();
+ logger.addAppender(consoleAppender);
+ logger.setLevel(Level.WARN);
+ // disable OWL API info output
+ java.util.logging.Logger.getLogger("").setLevel(java.util.logging.Level.WARNING);
+
+ new CrossValidation(file, folds, leaveOneOut);
+
+ }
+
+ public CrossValidation(File file, int folds, boolean leaveOneOut) {
+
+ DecimalFormat df = new DecimalFormat();
+ ComponentManager cm = ComponentManager.getInstance();
+
+ // the first read of the file is used to detect the examples
+ // and set up the splits correctly according to our validation
+ // method
+ Start start = null;
+ try {
+ start = new Start(file);
+ } catch (ComponentInitException e) {
+ // TODO Auto-generated catch block
+ e.printStackTrace();
+ }
+
+ LearningProblem lp = start.getLearningProblem();
+ ReasoningService rs = start.getReasoningService();
+
+ // the training and test sets used later on
+ List<Set<Individual>> trainingSetsPos = new LinkedList<Set<Individual>>();
+ List<Set<Individual>> trainingSetsNeg = new LinkedList<Set<Individual>>();
+ List<Set<Individual>> testSetsPos = new LinkedList<Set<Individual>>();
+ List<Set<Individual>> testSetsNeg = new LinkedList<Set<Individual>>();
+
+ if(lp instanceof PosNegLP) {
+
+ // get examples and shuffle them to
+ Set<Individual> posExamples = ((PosNegLP)lp).getPositiveExamples();
+ List<Individual> posExamplesList = new LinkedList<Individual>(posExamples);
+ Collections.shuffle(posExamplesList, new Random(1));
+ Set<Individual> negExamples = ((PosNegLP)lp).getNegativeExamples();
+ List<Individual> negExamplesList = new LinkedList<Individual>(negExamples);
+ Collections.shuffle(negExamplesList, new Random(2));
+
+ // sanity check whether nr. of folds makes sense for this benchmark
+ if(!leaveOneOut && (posExamples.size()<folds && negExamples.size()<folds)) {
+ System.out.println("The number of folds is higher than the number of "
+ + "positive/negative examples. This can result in empty test sets. Exiting.");
+ System.exit(0);
+ }
+
+ if(leaveOneOut) {
+ // note that leave-one-out is not identical to k-fold with
+ // k = nr. of examples in the current implementation, because
+ // with n folds and n examples there is no guarantee that a fold
+ // is never empty (this is an implementation issue)
+ int nrOfExamples = posExamples.size() + negExamples.size();
+ for(int i = 0; i < nrOfExamples; i++) {
+ // ...
+ }
+ System.out.println("Leave-one-out not supported yet.");
+ System.exit(1);
+ } else {
+ // calculating where to split the sets, ; note that we split
+ // positive and negative examples separately such that the
+ // distribution of positive and negative examples remains similar
+ // (note that there better but more complex ways to implement this,
+ // which guarantee that the sum of the elements of a fold for pos
+ // and neg differs by at most 1 - it can differ by 2 in our implementation,
+ // e.g. with 3 folds, 4 pos. examples, 4 neg. examples)
+ int[] splitsPos = calculateSplits(posExamples.size(),folds);
+ int[] splitsNeg = calculateSplits(negExamples.size(),folds);
+
+// System.out.println(splitsPos[0]);
+// System.out.println(splitsNeg[0]);
+
+ // calculating training and test sets
+ for(int i=0; i<folds; i++) {
+ Set<Individual> testPos = getTestingSet(posExamplesList, splitsPos, i);
+ Set<Individual> testNeg = getTestingSet(negExamplesList, splitsNeg, i);
+ testSetsPos.add(i, testPos);
+ testSetsNeg.add(i, testNeg);
+ trainingSetsPos.add(i, getTrainingSet(posExamples, testPos));
+ trainingSetsNeg.add(i, getTrainingSet(negExamples, testNeg));
+ }
+
+ }
+
+ } else if(lp instanceof PosOnlyLP) {
+ System.out.println("Cross validation for positive only learning not supported yet.");
+ System.exit(0);
+ // Set<Individual> posExamples = ((PosOnlyLP)lp).getPositiveExamples();
+ // int[] splits = calculateSplits(posExamples.size(),folds);
+ } else {
+ System.out.println("Cross validation for learning problem " + lp + " not supported.");
+ System.exit(0);
+ }
+
+ // statistical values
+ Stat runtime = new Stat();
+ Stat accuracy = new Stat();
+ Stat length = new Stat();
+
+ // run the algorithm
+ for(int currFold=0; currFold<folds; currFold++) {
+ // we always perform a full initialisation to make sure that
+ // no objects are reused
+ try {
+ start = new Start(file);
+ } catch (ComponentInitException e) {
+ // TODO Auto-generated catch block
+ e.printStackTrace();
+ }
+ lp = start.getLearningProblem();
+ Set<String> pos = Datastructures.individualSetToStringSet(trainingSetsPos.get(currFold));
+ Set<String> neg = Datastructures.individualSetToStringSet(trainingSetsNeg.get(currFold));
+ cm.applyConfigEntry(lp, "positiveExamples", pos);
+ cm.applyConfigEntry(lp, "negativeExamples", neg);
+// System.out.println("pos: " + pos.size());
+// System.out.println("neg: " + neg.size());
+// System.exit(0);
+
+ // es fehlt init zwischendurch
+
+ LearningAlgorithm la = start.getLearningAlgorithm();
+ // init again, because examples have changed
+ try {
+ la.init();
+ } catch (ComponentInitException e) {
+ // TODO Auto-generated catch block
+ e.printStackTrace();
+ }
+ long algorithmStartTime = System.nanoTime();
+ la.start();
+ long algorithmDuration = System.nanoTime() - algorithmStartTime;
+ runtime.addNumber(algorithmDuration/(double)1000000000);
+
+ Description concept = la.getBestSolution();
+
+ Set<Individual> tmp = rs.instanceCheck(concept, testSetsPos.get(currFold));
+ Set<Individual> tmp2 = Helper.difference(testSetsPos.get(currFold), tmp);
+ Set<Individual> tmp3 = rs.instanceCheck(concept, testSetsNeg.get(currFold));
+
+ System.out.println("test set errors pos: " + tmp2);
+ System.out.println("test set errors neg: " + tmp3);
+
+ // calculate training accuracies
+ int trainingCorrectPosClassified = getCorrectPosClassified(rs, concept, trainingSetsPos.get(currFold));
+ int trainingCorrectNegClassified = getCorrectNegClassified(rs, concept, trainingSetsNeg.get(currFold));
+ int trainingCorrectExamples = trainingCorrectPosClassified + trainingCorrectNegClassified;
+ double trainingAccuracy = 100*((double)trainingCorrectExamples/(trainingSetsPos.get(currFold).size()+
+ trainingSetsNeg.get(currFold).size()));
+
+ // calculate test accuracies
+ int correctPosClassified = getCorrectPosClassified(rs, concept, testSetsPos.get(currFold));
+ int correctNegClassified = getCorrectNegClassified(rs, concept, testSetsNeg.get(currFold));
+ int correctExamples = correctPosClassified + correctNegClassified;
+ double currAccuracy = 100*((double)correctExamples/(testSetsPos.get(currFold).size()+
+ testSetsNeg.get(currFold).size()));
+ accuracy.addNumber(currAccuracy);
+
+ length.addNumber(concept.getLength());
+
+ System.out.println("fold " + currFold + " (" + file + "):");
+ System.out.println(" training: " + pos.size() + " positive and " + neg.size() + " negative examples");
+ System.out.println(" testing: " + correctPosClassified + "/" + testSetsPos.get(currFold).size() + " correct positives, "
+ + correctNegClassified + "/" + testSetsNeg.get(currFold).size() + " correct negatives");
+ System.out.println(" concept: " + concept);
+ System.out.println(" accuracy: " + df.format(currAccuracy) + "% (" + df.format(trainingAccuracy) + "% on training set)");
+ System.out.println(" length: " + df.format(concept.getLength()));
+ System.out.println(" runtime: " + df.format(algorithmDuration/(double)1000000000) + "s");
+
+ // free all resources
+ start.getReasoningService().releaseKB();
+ cm.freeAllComponents();
+ }
+
+ System.out.println();
+ System.out.println("Finished " + folds + "-folds cross-validation on " + file + ".");
+ System.out.println("runtime: " + statOutput(df, runtime, "s"));
+ System.out.println("length: " + statOutput(df, length, ""));
+ System.out.println("accuracy: " + statOutput(df, accuracy, "%"));
+
+ }
+
+ private int getCorrectPosClassified(ReasoningService rs, Description concept, Set<Individual> testSetPos) {
+ return rs.instanceCheck(concept, testSetPos).size();
+ }
+
+ private int getCorrectNegClassified(ReasoningService rs, Description concept, Set<Individual> testSetNeg) {
+ return testSetNeg.size() - rs.instanceCheck(concept, testSetNeg).size();
+ }
+
+ private Set<Individual> getTestingSet(List<Individual> examples, int[] splits, int fold) {
+ int fromIndex;
+ // we either start from 0 or after the last fold ended
+ if(fold == 0)
+ fromIndex = 0;
+ else
+ fromIndex = splits[fold-1];
+ // the split corresponds to the ends of the folds
+ int toIndex = splits[fold];
+
+// System.out.println("from " + fromIndex + " to " + toIndex);
+
+ Set<Individual> testingSet = new HashSet<Individual>();
+ // +1 because 2nd element is exclusive in subList method
+ testingSet.addAll(examples.subList(fromIndex, toIndex));
+ return testingSet;
+ }
+
+ private Set<Individual> getTrainingSet(Set<Individual> examples, Set<Individual> testingSet) {
+ return Helper.difference(examples, testingSet);
+ }
+
+ // takes nr. of examples and the nr. of folds for this examples;
+ // returns an array which says where each fold ends, i.e.
+ // splits[i] is the index of the last element of fold i in the examples
+ private int[] calculateSplits(int nrOfExamples, int folds) {
+ int[] splits = new int[folds];
+ for(int i=1; i<=folds; i++) {
+ // we always round up to the next integer
+ splits[i-1] = (int)Math.ceil(i*nrOfExamples/(double)folds);
+ }
+ return splits;
+ }
+
+ private String statOutput(DecimalFormat df, Stat stat, String unit) {
+ String str = "av. " + df.format(stat.getMean()) + unit;
+ str += " (deviation " + df.format(stat.getStandardDeviation()) + unit + "; ";
+ str += "min " + df.format(stat.getMin()) + unit + "; ";
+ str += "max " + df.format(stat.getMax()) + unit + ")";
+ return str;
+ }
+
+}
Copied: trunk/src/dl-learner/org/dllearner/scripts/NT2RDF.java (from rev 808, trunk/src/dl-learner/org/dllearner/utilities/NT2RDF.java)
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/NT2RDF.java (rev 0)
+++ trunk/src/dl-learner/org/dllearner/scripts/NT2RDF.java 2008-04-22 15:23:38 UTC (rev 810)
@@ -0,0 +1,35 @@
+package org.dllearner.scripts;
+import java.io.File;
+import java.net.URI;
+
+import org.semanticweb.owl.apibinding.OWLManager;
+import org.semanticweb.owl.io.RDFXMLOntologyFormat;
+import org.semanticweb.owl.model.OWLOntology;
+import org.semanticweb.owl.model.OWLOntologyManager;
+public class NT2RDF {
+
+
+ public static void main(String[] args) {
+ try {
+ String ontopath=args[0];
+ URI inputURI = new File(ontopath).toURI();
+
+ // outputURI
+ String ending = ontopath.substring(ontopath.lastIndexOf(".") + 1);
+ ontopath = ontopath.replace("." + ending, ".rdf" );
+ URI outputURI = new File(ontopath).toURI();
+
+ OWLOntologyManager manager = OWLManager.createOWLOntologyManager();
+ OWLOntology ontology = manager.loadOntologyFromPhysicalURI(inputURI);
+ manager.saveOntology(ontology, new RDFXMLOntologyFormat(), outputURI);
+ // Remove the ontology from the manager
+ manager.removeOntology(ontology.getURI());
+ }
+ catch (Exception e) {
+ System.out.println("The ontology could not be created: " + e.getMessage());
+ }
+
+ }
+ }
+
+
Copied: trunk/src/dl-learner/org/dllearner/scripts/SPARQLPreparation.java (from rev 809, trunk/src/dl-learner/org/dllearner/test/SPARQLPreparation.java)
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/SPARQLPreparation.java (rev 0)
+++ trunk/src/dl-learner/org/dllearner/scripts/SPARQLPreparation.java 2008-04-22 15:23:38 UTC (rev 810)
@@ -0,0 +1,176 @@
+package org.dllearner.scripts;
+
+import java.util.Random;
+import java.util.SortedSet;
+import java.util.TreeSet;
+
+import javax.sound.midi.SysexMessage;
+
+import org.apache.log4j.ConsoleAppender;
+import org.apache.log4j.Level;
+import org.apache.log4j.Logger;
+import org.apache.log4j.SimpleLayout;
+import org.dllearner.kb.sparql.Cache;
+import org.dllearner.kb.sparql.SparqlQuery;
+import org.dllearner.kb.sparql.SparqlQueryDescriptionConvertVisitor;
+import org.dllearner.kb.sparql.configuration.SparqlEndpoint;
+import org.dllearner.utilities.ConfWriter;
+import org.dllearner.utilities.JenaResultSetConvenience;
+import org.dllearner.utilities.LearnSparql;
+import org.dllearner.utilities.SimpleClock;
+
+import com.hp.hpl.jena.query.ResultSet;
+
+public class SPARQLPreparation {
+
+ static Cache c;
+ static SparqlEndpoint se;
+ private static Logger logger = Logger.getRootLogger();
+ /**
+ * @param args
+ */
+ public static void main(String[] args) {
+ init();
+ try {
+
+
+
+ SimpleClock sc=new SimpleClock();
+ SortedSet<String> concepts = new TreeSet<String>();
+ //concepts.add("\"http://dbpedia.org/class/yago/Person100007846\"");
+ concepts.add("\"http://dbpedia.org/class/yago/FieldMarshal110086821\"");
+ SortedSet<String> posExamples = new TreeSet<String>();
+ SortedSet<String> negExamples = new TreeSet<String>();
+ String url = "http://dbpedia.openlinksw.com:8890/sparql";
+ //HashMap<String, ResultSet> result = new HashMap<String, ResultSet>();
+ //HashMap<String, String> result2 = new HashMap<String, String>();
+
+ //System.out.println(concepts.first());
+ posExamples = new JenaResultSetConvenience(queryConcept(concepts.first(),0))
+ .getStringListForVariable("subject");
+
+ for (String string : posExamples) {
+ negExamples.addAll( getObjects(string));
+ //if(neg.size()>=1)System.out.println(neg);
+ }
+
+ /*for (String string2 : negExamples) {
+ if(posExamples.contains(string2)){
+ System.out.println(string2);
+ negExamples.remove(string2);
+ };
+ }*/
+ //System.out.println(negExamples.size());
+ negExamples.removeAll(posExamples);
+ posExamples=shrink(posExamples,5);
+ negExamples=shrink(negExamples,posExamples.size());
+ //System.out.println(posExamples.first()));
+ //System.out.println(posExamples.size());
+ //System.out.println(negExamples.size());
+
+ //
+ new ConfWriter().writeSPARQL("aaa.conf", posExamples, negExamples, url, new TreeSet<String>());
+ new LearnSparql().learn(posExamples, negExamples, "http://dbpedia.openlinksw.com:8890/sparql", new TreeSet<String>());
+
+ sc.printAndSet("Finished");
+ } catch (Exception e) {
+ e.printStackTrace();
+
+ }
+
+ }
+
+ /***************************************************************************
+ * *********************OLDCODE String
+ * conj="(\"http://dbpedia.org/class/yago/Person100007846\" AND
+ * \"http://dbpedia.org/class/yago/Head110162991\")";
+ *
+ *
+ * concepts.add("EXISTS \"http://dbpedia.org/property/disambiguates\".TOP");
+ * concepts.add("EXISTS
+ * \"http://dbpedia.org/property/successor\".\"http://dbpedia.org/class/yago/Person100007846\"");
+ * concepts.add("EXISTS \"http://dbpedia.org/property/successor\"."+conj);
+ * //concepts.add("ALL \"http://dbpedia.org/property/disambiguates\".TOP");
+ * //concepts.add("ALL
+ * \"http://dbpedia.org/property/successor\".\"http://dbpedia.org/class/yago/Person100007846\"");
+ * concepts.add("\"http://dbpedia.org/class/yago/Person100007846\"");
+ * concepts.add(conj);
+ * concepts.add("(\"http://dbpedia.org/class/yago/Person100007846\" OR
+ * \"http://dbpedia.org/class/yago/Head110162991\")");
+ *
+ * //concepts.add("NOT \"http://dbpedia.org/class/yago/Person100007846\"");
+ *
+ * for (String kbsyntax : concepts) {
+ * result.put(kbsyntax,queryConcept(kbsyntax)); }
+ * System.out.println("************************"); for (String string :
+ * result.keySet()) { System.out.println("KBSyntayString: "+string);
+ * System.out.println("Query:\n"+result.get(string).hasNext());
+ * System.out.println("************************"); }
+ **************************************************************************/
+
+ static SortedSet<String> getObjects(String subject) {
+ // SortedSet<String> result = new TreeSet<String>();
+
+ String query = "SELECT * WHERE { \n" + "<" + subject + "> " + "?p ?o. \n"
+ + "FILTER (REGEX(str(?o), 'http://dbpedia.org/resource/')).\n"
+ + "FILTER (!REGEX(str(?p), 'http://www.w3.org/2004/02/skos'))\n"
+ + "}";
+ //System.out.println(query);
+ String JSON = (c.executeSparqlQuery(new SparqlQuery(query, se)));
+ //System.out.println(JSON);
+ ResultSet rs =SparqlQuery.JSONtoResultSet(JSON);
+ JenaResultSetConvenience rsc = new JenaResultSetConvenience(rs);
+ return rsc.getStringListForVariable("o");
+ }
+
+ public static ResultSet queryConcept(String concept,int limit) {
+ ResultSet rs = null;
+ try {
+ String query = SparqlQueryDescriptionConvertVisitor
+ .getSparqlQuery(concept,limit);
+
+ SparqlQuery sq = new SparqlQuery(query, se);
+ String JSON = c.executeSparqlQuery(sq);
+ //System.out.println(JSON);
+ rs = SparqlQuery.JSONtoResultSet(JSON);
+
+ } catch (Exception e) {
+ e.printStackTrace();
+ }
+
+ return rs;
+ }
+
+ public static void init() {
+ SparqlQueryDescriptionConvertVisitor.debug_flag = false;
+ c = new Cache("cache");
+ se = SparqlEndpoint.dbpediaEndpoint();
+ // create logger (a simple logger which outputs
+ // its messages to the console)
+ SimpleLayout layout = new SimpleLayout();
+ ConsoleAppender consoleAppender = new ConsoleAppender(layout);
+ logger.removeAllAppenders();
+ logger.addAppender(consoleAppender);
+ logger.setLevel(Level.DEBUG);
+
+
+ }
+
+ public static SortedSet<String> shrink(SortedSet<String> s, int limit) {
+ SortedSet<String> ret = new TreeSet<String>();
+ Random r = new Random();
+ double treshold = ((double)limit)/s.size();
+ //System.out.println("treshold"+howmany);
+ //System.out.println("treshold"+allRetrieved.size());
+ System.out.println("treshold"+treshold);
+
+ for (String oneInd : s) {
+ if(r.nextDouble()<treshold) {
+ ret.add(oneInd);
+
+ }
+ }
+ return ret;
+ }
+
+}
Deleted: trunk/src/dl-learner/org/dllearner/test/SPARQLPreparation.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/test/SPARQLPreparation.java 2008-04-22 15:19:07 UTC (rev 809)
+++ trunk/src/dl-learner/org/dllearner/test/SPARQLPreparation.java 2008-04-22 15:23:38 UTC (rev 810)
@@ -1,176 +0,0 @@
-package org.dllearner.test;
-
-import java.util.Random;
-import java.util.SortedSet;
-import java.util.TreeSet;
-
-import javax.sound.midi.SysexMessage;
-
-import org.apache.log4j.ConsoleAppender;
-import org.apache.log4j.Level;
-import org.apache.log4j.Logger;
-import org.apache.log4j.SimpleLayout;
-import org.dllearner.kb.sparql.Cache;
-import org.dllearner.kb.sparql.SparqlQuery;
-import org.dllearner.kb.sparql.SparqlQueryDescriptionConvertVisitor;
-import org.dllearner.kb.sparql.configuration.SparqlEndpoint;
-import org.dllearner.utilities.ConfWriter;
-import org.dllearner.utilities.JenaResultSetConvenience;
-import org.dllearner.utilities.LearnSparql;
-import org.dllearner.utilities.SimpleClock;
-
-import com.hp.hpl.jena.query.ResultSet;
-
-public class SPARQLPreparation {
-
- static Cache c;
- static SparqlEndpoint se;
- private static Logger logger = Logger.getRootLogger();
- /**
- * @param args
- */
- public static void main(String[] args) {
- init();
- try {
-
-
-
- SimpleClock sc=new SimpleClock();
- SortedSet<String> concepts = new TreeSet<String>();
- //concepts.add("\"http://dbpedia.org/class/yago/Person100007846\"");
- concepts.add("\"http://dbpedia.org/class/yago/FieldMarshal110086821\"");
- SortedSet<String> posExamples = new TreeSet<String>();
- SortedSet<String> negExamples = new TreeSet<String>();
- String url = "http://dbpedia.openlinksw.com:8890/sparql";
- //HashMap<String, ResultSet> result = new HashMap<String, ResultSet>();
- //HashMap<String, String> result2 = new HashMap<String, String>();
-
- //System.out.println(concepts.first());
- posExamples = new JenaResultSetConvenience(queryConcept(concepts.first(),0))
- .getStringListForVariable("subject");
-
- for (String string : posExamples) {
- negExamples.addAll( getObjects(string));
- //if(neg.size()>=1)System.out.println(neg);
- }
-
- /*for (String string2 : negExamples) {
- if(posExamples.contains(string2)){
- System.out.println(string2);
- negExamples.remove(string2);
- };
- }*/
- //System.out.println(negExamples.size());
- negExamples.removeAll(posExamples);
- posExamples=shrink(posExamples,5);
- negExamples=shrink(negExamples,posExamples.size());
- //System.out.println(posExamples.first()));
- //System.out.println(posExamples.size());
- //System.out.println(negExamples.size());
-
- //
- new ConfWriter().writeSPARQL("aaa.conf", posExamples, negExamples, url, new TreeSet<String>());
- new LearnSparql().learn(posExamples, negExamples, "http://dbpedia.openlinksw.com:8890/sparql", new TreeSet<String>());
-
- sc.printAndSet("Finished");
- } catch (Exception e) {
- e.printStackTrace();
-
- }
-
- }
-
- /***************************************************************************
- * *********************OLDCODE String
- * conj="(\"http://dbpedia.org/class/yago/Person100007846\" AND
- * \"http://dbpedia.org/class/yago/Head110162991\")";
- *
- *
- * concepts.add("EXISTS \"http://dbpedia.org/property/disambiguates\".TOP");
- * concepts.add("EXISTS
- * \"http://dbpedia.org/property/successor\".\"http://dbpedia.org/class/yago/Person100007846\"");
- * concepts.add("EXISTS \"http://dbpedia.org/property/successor\"."+conj);
- * //concepts.add("ALL \"http://dbpedia.org/property/disambiguates\".TOP");
- * //concepts.add("ALL
- * \"http://dbpedia.org/property/successor\".\"http://dbpedia.org/class/yago/Person100007846\"");
- * concepts.add("\"http://dbpedia.org/class/yago/Person100007846\"");
- * concepts.add(conj);
- * concepts.add("(\"http://dbpedia.org/class/yago/Person100007846\" OR
- * \"http://dbpedia.org/class/yago/Head110162991\")");
- *
- * //concepts.add("NOT \"http://dbpedia.org/class/yago/Person100007846\"");
- *
- * for (String kbsyntax : concepts) {
- * result.put(kbsyntax,queryConcept(kbsyntax)); }
- * System.out.println("************************"); for (String string :
- * result.keySet()) { System.out.println("KBSyntayString: "+string);
- * System.out.println("Query:\n"+result.get(string).hasNext());
- * System.out.println("************************"); }
- **************************************************************************/
-
- static SortedSet<String> getObjects(String subject) {
- // SortedSet<String> result = new TreeSet<String>();
-
- String query = "SELECT * WHERE { \n" + "<" + subject + "> " + "?p ?o. \n"
- + "FILTER (REGEX(str(?o), 'http://dbpedia.org/resource/')).\n"
- + "FILTER (!REGEX(str(?p), 'http://www.w3.org/2004/02/skos'))\n"
- + "}";
- //System.out.println(query);
- String JSON = (c.executeSparqlQuery(new SparqlQuery(query, se)));
- //System.out.println(JSON);
- ResultSet rs =SparqlQuery.JSONtoResultSet(JSON);
- JenaResultSetConvenience rsc = new JenaResultSetConvenience(rs);
- return rsc.getStringListForVariable("o");
- }
-
- public static ResultSet queryConcept(String concept,int limit) {
- ResultSet rs = null;
- try {
- String query = SparqlQueryDescriptionConvertVisitor
- .getSparqlQuery(concept,limit);
-
- SparqlQuery sq = new SparqlQuery(query, se);
- String JSON = c.executeSparqlQuery(sq);
- //System.out.println(JSON);
- rs = SparqlQuery.JSONtoResultSet(JSON);
-
- } catch (Exception e) {
- e.printStackTrace();
- }
-
- return rs;
- }
-
- public static void init() {
- SparqlQueryDescriptionConvertVisitor.debug_flag = false;
- c = new Cache("cache");
- se = SparqlEndpoint.dbpediaEndpoint();
- // create logger (a simple logger which outputs
- // its messages to the console)
- SimpleLayout layout = new SimpleLayout();
- ConsoleAppender consoleAppender = new ConsoleAppender(layout);
- logger.removeAllAppenders();
- logger.addAppender(consoleAppender);
- logger.setLevel(Level.DEBUG);
-
-
- }
-
- public static SortedSet<String> shrink(SortedSet<String> s, int limit) {
- SortedSet<String> ret = new TreeSet<String>();
- Random r = new Random();
- double treshold = ((double)limit)/s.size();
- //System.out.println("treshold"+howmany);
- //System.out.println("treshold"+allRetrieved.size());
- System.out.println("treshold"+treshold);
-
- for (String oneInd : s) {
- if(r.nextDouble()<treshold) {
- ret.add(oneInd);
-
- }
- }
- return ret;
- }
-
-}
Deleted: trunk/src/dl-learner/org/dllearner/utilities/CloseOntology.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/utilities/CloseOntology.java 2008-04-22 15:19:07 UTC (rev 809)
+++ trunk/src/dl-learner/org/dllearner/utilities/CloseOntology.java 2008-04-22 15:23:38 UTC (rev 810)
@@ -1,65 +0,0 @@
-package org.dllearner.utilities;
-
-import java.io.File;
-import java.net.URI;
-import java.util.HashSet;
-import java.util.Set;
-
-import org.dllearner.core.KnowledgeSource;
-import org.dllearner.kb.OWLFile;
-import org.dllearner.reasoning.OWLAPIReasoner;
-
-/**
- * Script for closing an ontology OWLAPI produces extensive filesizes, when
- * exporting output file ist named like input file, but recieves a
- * "_closedConcise" at the end.
- *
- * Counts all roles of individuals and adds an Intersection (Concise) of
- * ExactCardinalityRestriction to the ABox
- *
- */
-public class CloseOntology {
-
- /**
- * @param argument0
- * simply the path to the owl ontology "examples/test.owl"
- */
- public static void main(String[] args) {
- String ontopath="";
- //ontopath="examples/carcinogenesis/carcinogenesis.owl";
- // inputURI
- //ontopath = args[0];
- File file = new File(ontopath);
- URI inputURI = file.toURI();
-
- // outputURI
- String ending = ontopath.substring(ontopath.lastIndexOf(".") + 1);
- ontopath = ontopath.replace("." + ending, "_closedConcise." + ending);
- file = new File(ontopath);
- URI outputURI = file.toURI();
-
- try {
- // initializing reasoner
- OWLFile owlFile = new OWLFile();
- owlFile.setURL(inputURI.toURL());
- Set<KnowledgeSource> ks = new HashSet<KnowledgeSource>();
- ks.add(owlFile);
- OWLAPIReasoner owlapireasoner = new OWLAPIReasoner(ks);
- owlapireasoner.init();
-
- // close
- OntologyCloserOWLAPI oc = new OntologyCloserOWLAPI(owlapireasoner);
- oc.testForTransitiveProperties(true);
- System.out.println("Attempting to close");
- oc.applyNumberRestrictionsConcise();
- System.out.println("Finished, preparing output");
-
- // save
- oc.writeOWLFile(outputURI);
-
- } catch (Exception e) {
- e.printStackTrace();
- }
- }
-
-}
Deleted: trunk/src/dl-learner/org/dllearner/utilities/CrossValidation.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/utilities/CrossValidation.java 2008-04-22 15:19:07 UTC (rev 809)
+++ trunk/src/dl-learner/org/dllearner/utilities/CrossValidation.java 2008-04-22 15:23:38 UTC (rev 810)
@@ -1,315 +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.utilities;
-
-import java.io.File;
-import java.text.DecimalFormat;
-import java.util.Collections;
-import java.util.HashSet;
-import java.util.LinkedList;
-import java.util.List;
-import java.util.Random;
-import java.util.Set;
-
-import org.apache.log4j.ConsoleAppender;
-import org.apache.log4j.Level;
-import org.apache.log4j.Logger;
-import org.apache.log4j.SimpleLayout;
-import org.dllearner.cli.Start;
-import org.dllearner.core.ComponentInitException;
-import org.dllearner.core.ComponentManager;
-import org.dllearner.core.LearningAlgorithm;
-import org.dllearner.core.LearningProblem;
-import org.dllearner.core.ReasoningService;
-import org.dllearner.core.owl.Description;
-import org.dllearner.core.owl.Individual;
-import org.dllearner.learningproblems.PosNegLP;
-import org.dllearner.learningproblems.PosOnlyLP;
-
-/**
- * Performs cross validation for the given problem. Supports
- * k-fold cross-validation and leave-one-out cross-validation.
- *
- * @author Jens Lehmann
- *
- */
-public class CrossValidation {
-
- private static Logger logger = Logger.getRootLogger();
-
- public static void main(String[] args) {
- File file = new File(args[0]);
-
- boolean leaveOneOut = false;
- int folds = 10;
-
- // use second argument as number of folds; if not specified
- // leave one out cross validation is used
- if(args.length > 1)
- folds = Integer.parseInt(args[1]);
- else
- leaveOneOut = true;
-
- if(folds < 2) {
- System.out.println("At least 2 fold needed.");
- System.exit(0);
- }
-
- // create logger (a simple logger which outputs
- // its messages to the console)
- SimpleLayout layout = new SimpleLayout();
- ConsoleAppender consoleAppender = new ConsoleAppender(layout);
- logger.removeAllAppenders();
- logger.addAppender(consoleAppender);
- logger.setLevel(Level.WARN);
- // disable OWL API info output
- java.util.logging.Logger.getLogger("").setLevel(java.util.logging.Level.WARNING);
-
- new CrossValidation(file, folds, leaveOneOut);
-
- }
-
- public CrossValidation(File file, int folds, boolean leaveOneOut) {
-
- DecimalFormat df = new DecimalFormat();
- ComponentManager cm = ComponentManager.getInstance();
-
- // the first read of the file is used to detect the examples
- // and set up the splits correctly according to our validation
- // method
- Start start = null;
- try {
- start = new Start(file);
- } catch (ComponentInitException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- }
-
- LearningProblem lp = start.getLearningProblem();
- ReasoningService rs = start.getReasoningService();
-
- // the training and test sets used later on
- List<Set<Individual>> trainingSetsPos = new LinkedList<Set<Individual>>();
- List<Set<Individual>> trainingSetsNeg = new LinkedList<Set<Individual>>();
- List<Set<Individual>> testSetsPos = new LinkedList<Set<Individual>>();
- List<Set<Individual>> testSetsNeg = new LinkedList<Set<Individual>>();
-
- if(lp instanceof PosNegLP) {
-
- // get examples and shuffle them to
- Set<Individual> posExamples = ((PosNegLP)lp).getPositiveExamples();
- List<Individual> posExamplesList = new LinkedList<Individual>(posExamples);
- Collections.shuffle(posExamplesList, new Random(1));
- Set<Individual> negExamples = ((PosNegLP)lp).getNegativeExamples();
- List<Individual> negExamplesList = new LinkedList<Individual>(negExamples);
- Collections.shuffle(negExamplesList, new Random(2));
-
- // sanity check whether nr. of folds makes sense for this benchmark
- if(!leaveOneOut && (posExamples.size()<folds && negExamples.size()<folds)) {
- System.out.println("The number of folds is higher than the number of "
- + "positive/negative examples. This can result in empty test sets. Exiting.");
- System.exit(0);
- }
-
- if(leaveOneOut) {
- // note that leave-one-out is not identical to k-fold with
- // k = nr. of examples in the current implementation, because
- // with n folds and n examples there is no guarantee that a fold
- // is never empty (this is an implementation issue)
- int nrOfExamples = posExamples.size() + negExamples.size();
- for(int i = 0; i < nrOfExamples; i++) {
- // ...
- }
- System.out.println("Leave-one-out not supported yet.");
- System.exit(1);
- } else {
- // calculating where to split the sets, ; note that we split
- // positive and negative examples separately such that the
- // distribution of positive and negative examples remains similar
- // (note that there better but more complex ways to implement this,
- // which guarantee that the sum of the elements of a fold for pos
- // and neg differs by at most 1 - it can differ by 2 in our implementation,
- // e.g. with 3 folds, 4 pos. examples, 4 neg. examples)
- int[] splitsPos = calculateSplits(posExamples.size(),folds);
- int[] splitsNeg = calculateSplits(negExamples.size(),folds);
-
-// System.out.println(splitsPos[0]);
-// System.out.println(splitsNeg[0]);
-
- // calculating training and test sets
- for(int i=0; i<folds; i++) {
- Set<Individual> testPos = getTestingSet(posExamplesList, splitsPos, i);
- Set<Individual> testNeg = getTestingSet(negExamplesList, splitsNeg, i);
- testSetsPos.add(i, testPos);
- testSetsNeg.add(i, testNeg);
- trainingSetsPos.add(i, getTrainingSet(posExamples, testPos));
- trainingSetsNeg.add(i, getTrainingSet(negExamples, testNeg));
- }
-
- }
-
- } else if(lp instanceof PosOnlyLP) {
- System.out.println("Cross validation for positive only learning not supported yet.");
- System.exit(0);
- // Set<Individual> posExamples = ((PosOnlyLP)lp).getPositiveExamples();
- // int[] splits = calculateSplits(posExamples.size(),folds);
- } else {
- System.out.println("Cross validation for learning problem " + lp + " not supported.");
- System.exit(0);
- }
-
- // statistical values
- Stat runtime = new Stat();
- Stat accuracy = new Stat();
- Stat length = new Stat();
-
- // run the algorithm
- for(int currFold=0; currFold<folds; currFold++) {
- // we always perform a full initialisation to make sure that
- // no objects are reused
- try {
- start = new Start(file);
- } catch (ComponentInitException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- }
- lp = start.getLearningProblem();
- Set<String> pos = Datastructures.individualSetToStringSet(trainingSetsPos.get(currFold));
- Set<String> neg = Datastructures.individualSetToStringSet(trainingSetsNeg.get(currFold));
- cm.applyConfigEntry(lp, "positiveExamples", pos);
- cm.applyConfigEntry(lp, "negativeExamples", neg);
-// System.out.println("pos: " + pos.size());
-// System.out.println("neg: " + neg.size());
-// System.exit(0);
-
- // es fehlt init zwischendurch
-
- LearningAlgorithm la = start.getLearningAlgorithm();
- // init again, because examples have changed
- try {
- la.init();
- } catch (ComponentInitException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- }
- long algorithmStartTime = System.nanoTime();
- la.start();
- long algorithmDuration = System.nanoTime() - algorithmStartTime;
- runtime.addNumber(algorithmDuration/(double)1000000000);
-
- Description concept = la.getBestSolution();
-
- Set<Individual> tmp = rs.instanceCheck(concept, testSetsPos.get(currFold));
- Set<Individual> tmp2 = Helper.difference(testSetsPos.get(currFold), tmp);
- Set<Individual> tmp3 = rs.instanceCheck(concept, testSetsNeg.get(currFold));
-
- System.out.println("test set errors pos: " + tmp2);
- System.out.println("test set errors neg: " + tmp3);
-
- // calculate training accuracies
- int trainingCorrectPosClassified = getCorrectPosClassified(rs, concept, trainingSetsPos.get(currFold));
- int trainingCorrectNegClassified = getCorrectNegClassified(rs, concept, trainingSetsNeg.get(currFold));
- int trainingCorrectExamples = trainingCorrectPosClassified + trainingCorrectNegClassified;
- double trainingAccuracy = 100*((double)trainingCorrectExamples/(trainingSetsPos.get(currFold).size()+
- trainingSetsNeg.get(currFold).size()));
-
- // calculate test accuracies
- int correctPosClassified = getCorrectPosClassified(rs, concept, testSetsPos.get(currFold));
- int correctNegClassified = getCorrectNegClassified(rs, concept, testSetsNeg.get(currFold));
- int correctExamples = correctPosClassified + correctNegClassified;
- double currAccuracy = 100*((double)correctExamples/(testSetsPos.get(currFold).size()+
- testSetsNeg.get(currFold).size()));
- accuracy.addNumber(currAccuracy);
-
- length.addNumber(concept.getLength());
-
- System.out.println("fold " + currFold + " (" + file + "):");
- System.out.println(" training: " + pos.size() + " positive and " + neg.size() + " negative examples");
- System.out.println(" testing: " + correctPosClassified + "/" + testSetsPos.get(currFold).size() + " correct positives, "
- + correctNegClassified + "/" + testSetsNeg.get(currFold).size() + " correct negatives");
- System.out.println(" concept: " + concept);
- System.out.println(" accuracy: " + df.format(currAccuracy) + "% (" + df.format(trainingAccuracy) + "% on training set)");
- System.out.println(" length: " + df.format(concept.getLength()));
- System.out.println(" runtime: " + df.format(algorithmDuration/(double)1000000000) + "s");
-
- // free all resources
- start.getReasoningService().releaseKB();
- cm.freeAllComponents();
- }
-
- System.out.println();
- System.out.println("Finished " + folds + "-folds cross-validation on " + file + ".");
- System.out.println("runtime: " + statOutput(df, runtime, "s"));
- System.out.println("length: " + statOutput(df, length, ""));
- System.out.println("accuracy: " + statOutput(df, accuracy, "%"));
-
- }
-
- private int getCorrectPosClassified(ReasoningService rs, Description concept, Set<Individual> testSetPos) {
- return rs.instanceCheck(concept, testSetPos).size();
- }
-
- private int getCorrectNegClassified(ReasoningService rs, Description concept, Set<Individual> testSetNeg) {
- return testSetNeg.size() - rs.instanceCheck(concept, testSetNeg).size();
- }
-
- private Set<Individual> getTestingSet(List<Individual> examples, int[] splits, int fold) {
- int fromIndex;
- // we either start from 0 or after the last fold ended
- if(fold == 0)
- fromIndex = 0;
- else
- fromIndex = splits[fold-1];
- // the split corresponds to the ends of the folds
- int toIndex = splits[fold];
-
-// System.out.println("from " + fromIndex + " to " + toIndex);
-
- Set<Individual> testingSet = new HashSet<Individual>();
- // +1 because 2nd element is exclusive in subList method
- testingSet.addAll(examples.subList(fromIndex, toIndex));
- return testingSet;
- }
-
- private Set<Individual> getTrainingSet(Set<Individual> examples, Set<Individual> testingSet) {
- return Helper.difference(examples, testingSet);
- }
-
- // takes nr. of examples and the nr. of folds for this examples;
- // returns an array which says where each fold ends, i.e.
- // splits[i] is the index of the last element of fold i in the examples
- private int[] calculateSplits(int nrOfExamples, int folds) {
- int[] splits = new int[folds];
- for(int i=1; i<=folds; i++) {
- // we always round up to the next integer
- splits[i-1] = (int)Math.ceil(i*nrOfExamples/(double)folds);
- }
- return splits;
- }
-
- private String statOutput(DecimalFormat df, Stat stat, String unit) {
- String str = "av. " + df.format(stat.getMean()) + unit;
- str += " (deviation " + df.format(stat.getStandardDeviation()) + unit + "; ";
- str += "min " + df.format(stat.getMin()) + unit + "; ";
- str += "max " + df.format(stat.getMax()) + unit + ")";
- return str;
- }
-
-}
Deleted: trunk/src/dl-learner/org/dllearner/utilities/NT2RDF.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/utilities/NT2RDF.java 2008-04-22 15:19:07 UTC (rev 809)
+++ trunk/src/dl-learner/org/dllearner/utilities/NT2RDF.java 2008-04-22 15:23:38 UTC (rev 810)
@@ -1,35 +0,0 @@
-package org.dllearner.utilities;
-import java.io.File;
-import java.net.URI;
-
-import org.semanticweb.owl.apibinding.OWLManager;
-import org.semanticweb.owl.io.RDFXMLOntologyFormat;
-import org.semanticweb.owl.model.OWLOntology;
-import org.semanticweb.owl.model.OWLOntologyManager;
-public class NT2RDF {
-
-
- public static void main(String[] args) {
- try {
- String ontopath=args[0];
- URI inputURI = new File(ontopath).toURI();
-
- // outputURI
- String ending = ontopath.substring(ontopath.lastIndexOf(".") + 1);
- ontopath = ontopath.replace("." + ending, ".rdf" );
- URI outputURI = new File(ontopath).toURI();
-
- OWLOntologyManager manager = OWLManager.createOWLOntologyManager();
- OWLOntology ontology = manager.loadOntologyFromPhysicalURI(inputURI);
- manager.saveOntology(ontology, new RDFXMLOntologyFormat(), outputURI);
- // Remove the ontology from the manager
- manager.removeOntology(ontology.getURI());
- }
- catch (Exception e) {
- System.out.println("The ontology could not be created: " + e.getMessage());
- }
-
- }
- }
-
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