[DL-Learner SVN] SF.net SVN: dl-learner: [80] trunk/src/dl-learner/org/dllearner/utilities/ PaperStatistics.java

[<jen...@us...>]

Revision: 80
          http://dl-learner.svn.sourceforge.net/dl-learner/?rev=80&view=rev
Author:   jenslehmann
Date:     2007-08-28 03:57:53 -0700 (Tue, 28 Aug 2007)

Log Message:
-----------
added script for generating statistics (initial test version)

Added Paths:
-----------
    trunk/src/dl-learner/org/dllearner/utilities/PaperStatistics.java

Added: trunk/src/dl-learner/org/dllearner/utilities/PaperStatistics.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/utilities/PaperStatistics.java	                        (rev 0)
+++ trunk/src/dl-learner/org/dllearner/utilities/PaperStatistics.java	2007-08-28 10:57:53 UTC (rev 80)
@@ -0,0 +1,121 @@
+/**
+ * Copyright (C) 2007, 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.net.MalformedURLException;
+import java.net.URL;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.SortedSet;
+import java.util.TreeSet;
+
+import org.dllearner.Config;
+import org.dllearner.LearningProblem;
+import org.dllearner.Main;
+import org.dllearner.OntologyFileFormat;
+import org.dllearner.algorithms.refinement.ROLearner;
+import org.dllearner.dl.AtomicConcept;
+import org.dllearner.dl.Individual;
+import org.dllearner.dl.KB;
+import org.dllearner.parser.DLLearner;
+import org.dllearner.reasoning.Reasoner;
+import org.dllearner.reasoning.ReasoningMethodUnsupportedException;
+import org.dllearner.reasoning.ReasoningService;
+
+/**
+ * Utility script for creating statistics for publications.
+ * (Warning: Scripts may run for several hours.)
+ * 
+ * @author Jens Lehmann
+ *
+ */
+public class PaperStatistics {
+
+	/**
+	 * Points to the current statistic generation function.
+	 * 
+	 * @param args None.
+	 */
+	public static void main(String[] args) {
+		createStatistics();
+	}
+	
+	@SuppressWarnings("unused")
+	private static void createStatistics() {
+		
+		// set reasoner URL
+		try {
+			Config.digReasonerURL = new URL("http://localhost:8081");
+		} catch (MalformedURLException e) {
+			e.printStackTrace();
+		}			
+		
+		// used OWL files
+		File fatherOwlFile = new File("examples/father.owl");
+		String fatherConfFile = "examples/father2.conf";
+		URL ontologyFatherURL = null;
+		try {
+			ontologyFatherURL = new URL("file", "localhost", fatherOwlFile.getAbsolutePath());
+		} catch (MalformedURLException e1) {
+			e1.printStackTrace();
+		}
+		
+		Map<URL, OntologyFileFormat> m = new HashMap<URL, OntologyFileFormat>();
+		m.put(ontologyFatherURL, OntologyFileFormat.RDF_XML);
+		
+		// initialise reasoner
+		Reasoner reasoner = Main.createReasoner(new KB(), m);
+		ReasoningService rs = new ReasoningService(reasoner);		
+		
+		Main.autoDetectConceptsAndRoles(rs);
+		if (Config.Refinement.improveSubsumptionHierarchy) {
+			try {
+				reasoner.prepareSubsumptionHierarchy();
+				reasoner.prepareRoleHierarchy();
+				reasoner.getSubsumptionHierarchy().improveSubsumptionHierarchy();
+			} catch (ReasoningMethodUnsupportedException e) {
+				e.printStackTrace();
+			}
+		}
+		
+		// file is parsed, but we use only the specified examples really
+		// (everything else is ignored)
+		DLLearner.parseFile(fatherConfFile);
+		
+		SortedSet<Individual> positiveExamples = new TreeSet<Individual>();
+		SortedSet<Individual> negativeExamples = new TreeSet<Individual>();
+		Map<AtomicConcept,SortedSet<Individual>> posExamplesTmp = DLLearner.getPositiveExamples();
+		Map<AtomicConcept,SortedSet<Individual>> negExamplesTmp = DLLearner.getNegativeExamples();
+		
+		for (AtomicConcept target : posExamplesTmp.keySet())
+			positiveExamples = posExamplesTmp.get(target);
+
+		for (AtomicConcept target : negExamplesTmp.keySet())
+			negativeExamples = negExamplesTmp.get(target);
+		
+		LearningProblem learningProblem = new LearningProblem(rs, positiveExamples, negativeExamples);
+		ROLearner learner = new ROLearner(learningProblem);
+		learner.start();
+		System.out.println(learner.getBestSolution().toString());
+		
+	}
+	
+}


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