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[DL-Learner SVN] SF.net SVN: dl-learner:[3674] trunk/scripts/src/main/java/org/dllearner/ scripts/evaluation/EnrichmentEvaluation.java
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From: <lor...@us...> - 2012-05-02 09:27:00
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Revision: 3674
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=3674&view=rev
Author: lorenz_b
Date: 2012-05-02 09:26:50 +0000 (Wed, 02 May 2012)
Log Message:
-----------
Made script more flexible from command line and added algorithms.
Modified Paths:
--------------
trunk/scripts/src/main/java/org/dllearner/scripts/evaluation/EnrichmentEvaluation.java
Modified: trunk/scripts/src/main/java/org/dllearner/scripts/evaluation/EnrichmentEvaluation.java
===================================================================
--- trunk/scripts/src/main/java/org/dllearner/scripts/evaluation/EnrichmentEvaluation.java 2012-05-01 07:53:23 UTC (rev 3673)
+++ trunk/scripts/src/main/java/org/dllearner/scripts/evaluation/EnrichmentEvaluation.java 2012-05-02 09:26:50 UTC (rev 3674)
@@ -19,7 +19,10 @@
*/
package org.dllearner.scripts.evaluation;
+import static java.util.Arrays.asList;
+
import java.io.BufferedInputStream;
+import java.io.BufferedOutputStream;
import java.io.BufferedWriter;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
@@ -31,9 +34,11 @@
import java.io.FileWriter;
import java.io.IOException;
import java.io.InputStream;
+import java.io.StringWriter;
import java.lang.reflect.InvocationTargetException;
import java.net.MalformedURLException;
import java.net.SocketTimeoutException;
+import java.net.URI;
import java.net.URL;
import java.sql.Connection;
import java.sql.DriverManager;
@@ -60,6 +65,10 @@
import java.util.TreeSet;
import java.util.prefs.Preferences;
+import joptsimple.OptionException;
+import joptsimple.OptionParser;
+import joptsimple.OptionSet;
+
import org.apache.commons.compress.compressors.CompressorException;
import org.apache.commons.compress.compressors.CompressorInputStream;
import org.apache.commons.compress.compressors.CompressorStreamFactory;
@@ -70,14 +79,17 @@
import org.dllearner.algorithms.DisjointClassesLearner;
import org.dllearner.algorithms.SimpleSubclassLearner;
import org.dllearner.algorithms.celoe.CELOE;
+import org.dllearner.algorithms.properties.AsymmetricObjectPropertyAxiomLearner;
import org.dllearner.algorithms.properties.DataPropertyDomainAxiomLearner;
import org.dllearner.algorithms.properties.DataPropertyRangeAxiomLearner;
import org.dllearner.algorithms.properties.DisjointDataPropertyAxiomLearner;
+import org.dllearner.algorithms.properties.DisjointObjectPropertyAxiomLearner;
import org.dllearner.algorithms.properties.EquivalentDataPropertyAxiomLearner;
import org.dllearner.algorithms.properties.EquivalentObjectPropertyAxiomLearner;
import org.dllearner.algorithms.properties.FunctionalDataPropertyAxiomLearner;
import org.dllearner.algorithms.properties.FunctionalObjectPropertyAxiomLearner;
import org.dllearner.algorithms.properties.InverseFunctionalObjectPropertyAxiomLearner;
+import org.dllearner.algorithms.properties.InverseObjectPropertyAxiomLearner;
import org.dllearner.algorithms.properties.IrreflexiveObjectPropertyAxiomLearner;
import org.dllearner.algorithms.properties.ObjectPropertyDomainAxiomLearner;
import org.dllearner.algorithms.properties.ObjectPropertyRangeAxiomLearner;
@@ -107,6 +119,7 @@
import org.dllearner.core.owl.ObjectProperty;
import org.dllearner.core.owl.SubClassAxiom;
import org.dllearner.kb.SparqlEndpointKS;
+import org.dllearner.kb.sparql.ExtractionDBCache;
import org.dllearner.kb.sparql.SPARQLTasks;
import org.dllearner.kb.sparql.SparqlEndpoint;
import org.dllearner.kb.sparql.SparqlKnowledgeSource;
@@ -125,7 +138,6 @@
import org.dllearner.utilities.owl.OWLAPIConverter;
import org.ini4j.IniPreferences;
import org.ini4j.InvalidFileFormatException;
-import org.semanticweb.HermiT.Reasoner;
import org.semanticweb.owlapi.apibinding.OWLManager;
import org.semanticweb.owlapi.io.RDFXMLOntologyFormat;
import org.semanticweb.owlapi.model.AxiomType;
@@ -182,13 +194,12 @@
// only axioms with a score above this threshold will be considered
private double threshold = 0.7;
- private SparqlEndpoint endpoint = SparqlEndpoint.getEndpointDBpedia();
-// private SparqlEndpoint endpoint = SparqlEndpoint.getEndpointDBpedia();
+ private SparqlEndpoint endpoint;
// can be used to only evaluate a part of DBpedia
- private int maxObjectProperties = 0;
- private int maxDataProperties = 0;
- private int maxClasses = 0;
+ private int maxObjectProperties = 1;
+ private int maxDataProperties = 1;
+ private int maxClasses = 1;
private List<Class<? extends AxiomLearningAlgorithm>> objectPropertyAlgorithms;
private List<Class<? extends AxiomLearningAlgorithm>> dataPropertyAlgorithms;
private List<Class<? extends LearningAlgorithm>> classAlgorithms;
@@ -202,16 +213,19 @@
private OWLOntology dbPediaOntology;
private OWLReasoner reasoner;
private OWLDataFactory factory = new OWLDataFactoryImpl();
-
- public EnrichmentEvaluation() {
-
+
+ private SPARQLReasoner sparqlReasoner;
+
+ public EnrichmentEvaluation(SparqlEndpoint endpoint) {
+ this.endpoint = endpoint;
+
prefixes = new HashMap<String,String>();
prefixes.put("dbp","http://dbpedia.org/property/");
prefixes.put("dbo","http://dbpedia.org/ontology/");
prefixes.put("yago", "http://dbpedia.org/class/");
objectPropertyAlgorithms = new LinkedList<Class<? extends AxiomLearningAlgorithm>>();
-// objectPropertyAlgorithms.add(DisjointObjectPropertyAxiomLearner.class);
+ objectPropertyAlgorithms.add(DisjointObjectPropertyAxiomLearner.class);
objectPropertyAlgorithms.add(EquivalentObjectPropertyAxiomLearner.class);
objectPropertyAlgorithms.add(FunctionalObjectPropertyAxiomLearner.class);
objectPropertyAlgorithms.add(InverseFunctionalObjectPropertyAxiomLearner.class);
@@ -219,12 +233,14 @@
objectPropertyAlgorithms.add(ObjectPropertyRangeAxiomLearner.class);
objectPropertyAlgorithms.add(SubObjectPropertyOfAxiomLearner.class);
objectPropertyAlgorithms.add(SymmetricObjectPropertyAxiomLearner.class);
+ objectPropertyAlgorithms.add(AsymmetricObjectPropertyAxiomLearner.class);
objectPropertyAlgorithms.add(TransitiveObjectPropertyAxiomLearner.class);
objectPropertyAlgorithms.add(IrreflexiveObjectPropertyAxiomLearner.class);
objectPropertyAlgorithms.add(ReflexiveObjectPropertyAxiomLearner.class);
+ objectPropertyAlgorithms.add(InverseObjectPropertyAxiomLearner.class);
dataPropertyAlgorithms = new LinkedList<Class<? extends AxiomLearningAlgorithm>>();
-// dataPropertyAlgorithms.add(DisjointDataPropertyAxiomLearner.class);
+ dataPropertyAlgorithms.add(DisjointDataPropertyAxiomLearner.class);
dataPropertyAlgorithms.add(EquivalentDataPropertyAxiomLearner.class);
dataPropertyAlgorithms.add(FunctionalDataPropertyAxiomLearner.class);
dataPropertyAlgorithms.add(DataPropertyDomainAxiomLearner.class);
@@ -301,26 +317,36 @@
}
- public void start() throws IllegalArgumentException, SecurityException, InstantiationException,
+ public void start(boolean runClassAlgorithms, boolean runObjectPropertyAlgorithms, boolean runDataPropertyAlgorithms) throws IllegalArgumentException, SecurityException, InstantiationException,
IllegalAccessException, InvocationTargetException, NoSuchMethodException,
ComponentInitException, InterruptedException {
-// dropAndCreateTable();
long overallStartTime = System.currentTimeMillis();
SparqlEndpointKS ks = new SparqlEndpointKS(endpoint);
ks.init();
-// evaluateObjectProperties(ks);
+ sparqlReasoner = new SPARQLReasoner(ks);
+ sparqlReasoner.setCache(new ExtractionDBCache("cache"));
+ sparqlReasoner.prepareSubsumptionHierarchy();
Thread.sleep(20000);
+ if(runClassAlgorithms){
+ evaluateClasses(ks);
+ }
-// evaluateDataProperties(ks);
-//
-// Thread.sleep(20000);
+ Thread.sleep(20000);
- evaluateClasses(ks);
+ if(runObjectPropertyAlgorithms){
+ evaluateObjectProperties(ks);
+ }
+ Thread.sleep(20000);
+
+ if(runDataPropertyAlgorithms){
+ evaluateDataProperties(ks);
+ }
+
System.out.println("Overall runtime: " + (System.currentTimeMillis()-overallStartTime)/1000 + "s.");
}
@@ -338,6 +364,7 @@
// dynamically invoke constructor with SPARQL knowledge source
AxiomLearningAlgorithm learner = algorithmClass.getConstructor(
SparqlEndpointKS.class).newInstance(ks);
+ ((AbstractAxiomLearningAlgorithm)learner).setReasoner(sparqlReasoner);
ConfigHelper.configure(learner, "propertyToDescribe", property.toString());
ConfigHelper.configure(learner, "maxExecutionTimeInSeconds",
maxExecutionTimeInSeconds);
@@ -390,7 +417,7 @@
}
}
objectProperties++;
- if (maxObjectProperties != 0 && objectProperties > maxObjectProperties) {
+ if (maxObjectProperties != 0 && objectProperties == maxObjectProperties) {
break;
}
@@ -410,11 +437,12 @@
Thread.sleep(10000);
String algName = "";
for (DatatypeProperty property : properties) {
-
+ Thread.sleep(1000);
try{
// dynamically invoke constructor with SPARQL knowledge source
AxiomLearningAlgorithm learner = algorithmClass.getConstructor(
SparqlEndpointKS.class).newInstance(ks);
+ ((AbstractAxiomLearningAlgorithm)learner).setReasoner(sparqlReasoner);
ConfigHelper.configure(learner, "propertyToDescribe", property.toString());
ConfigHelper.configure(learner, "maxExecutionTimeInSeconds",
maxExecutionTimeInSeconds);
@@ -466,7 +494,7 @@
}
}
dataProperties++;
- if (maxDataProperties != 0 && dataProperties > maxDataProperties) {
+ if (maxDataProperties != 0 && dataProperties == maxDataProperties) {
break;
}
@@ -499,6 +527,7 @@
// dynamically invoke constructor with SPARQL knowledge source
LearningAlgorithm learner = algorithmClass.getConstructor(
SparqlEndpointKS.class).newInstance(ks);
+ ((AbstractAxiomLearningAlgorithm)learner).setReasoner(sparqlReasoner);
ConfigHelper.configure(learner, "classToDescribe", cls.toString());
ConfigHelper.configure(learner, "maxExecutionTimeInSeconds",
maxExecutionTimeInSeconds);
@@ -548,7 +577,7 @@
}
classesCnt++;
- if (maxClasses != 0 && classesCnt > maxClasses) {
+ if (maxClasses != 0 && classesCnt == maxClasses) {
break;
}
@@ -689,7 +718,7 @@
int numberOfEntitiesWithTimeout = rs.getInt(1);
//compute average number of suggestions above threshold
- ps = conn.prepareStatement("SELECT AVG(cnt) FROM (SELECT entity, COUNT(axiom) AS cnt FROM (SELECT * FROM evaluation WHERE algorithm=? AND score >=?) AS A GROUP BY entity) AS B");
+ ps = conn.prepareStatement("SELECT AVG(cnt) FROM (SELECT entity, COUNT(DISTINCT axiom) AS cnt FROM (SELECT * FROM evaluation WHERE algorithm=? AND score >=?) AS A GROUP BY entity) AS B");
ps.setString(1, algoName);
ps.setDouble(2, threshold);
rs = ps.executeQuery();
@@ -734,6 +763,7 @@
}
table1.append("\\bottomrule\n\\end{tabulary}");
System.out.println(table1.toString());
+ write2Disk(table1.toString(), "evaluation/table1.tex");
//second part of evaluation
@@ -821,6 +851,7 @@
table2.append("\\end{tabulary}");
System.out.println(table2.toString());
+ write2Disk(table2.toString(), "evaluation/table2.tex");
}
private void writeToDisk(AxiomType<? extends OWLAxiom> axiomType, Map<String, Double> axiomsWithAccurracy){
@@ -862,6 +893,19 @@
}
}
+ private void write2Disk(String content, String file){
+ try {
+ new File(file).createNewFile();
+ BufferedOutputStream bos = new BufferedOutputStream(new FileOutputStream(file));
+ bos.write(content.getBytes());
+ bos.close();
+ } catch (FileNotFoundException e) {
+ e.printStackTrace();
+ } catch (IOException e) {
+ e.printStackTrace();
+ }
+ }
+
private void writeToDisk(AxiomType<? extends OWLAxiom> axiomType, Set<String> axioms){
String fileName = axiomType.getName().replaceAll(" ", "_") + ".txt";
@@ -920,8 +964,10 @@
axiomType2Algorithm.put(AxiomType.FUNCTIONAL_OBJECT_PROPERTY, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{FunctionalObjectPropertyAxiomLearner.class}));
axiomType2Algorithm.put(AxiomType.INVERSE_FUNCTIONAL_OBJECT_PROPERTY, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{InverseFunctionalObjectPropertyAxiomLearner.class}));
axiomType2Algorithm.put(AxiomType.SYMMETRIC_OBJECT_PROPERTY, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{SymmetricObjectPropertyAxiomLearner.class}));
+ axiomType2Algorithm.put(AxiomType.ASYMMETRIC_OBJECT_PROPERTY, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{AsymmetricObjectPropertyAxiomLearner.class}));
axiomType2Algorithm.put(AxiomType.REFLEXIVE_OBJECT_PROPERTY, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{ReflexiveObjectPropertyAxiomLearner.class}));
axiomType2Algorithm.put(AxiomType.IRREFLEXIVE_OBJECT_PROPERTY, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{IrreflexiveObjectPropertyAxiomLearner.class}));
+ axiomType2Algorithm.put(AxiomType.INVERSE_OBJECT_PROPERTIES, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{InverseObjectPropertyAxiomLearner.class}));
axiomType2Algorithm.put(AxiomType.SUB_DATA_PROPERTY, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{SubDataPropertyOfAxiomLearner.class}));
axiomType2Algorithm.put(AxiomType.EQUIVALENT_DATA_PROPERTIES, Arrays.asList((Class<? extends LearningAlgorithm>[])new Class[]{EquivalentDataPropertyAxiomLearner.class}));
@@ -1127,18 +1173,99 @@
}
public static void main(String[] args) throws Exception
-
+
{
- EnrichmentEvaluation ee = new EnrichmentEvaluation();
- ee.dropAndCreateTable();
- ee.start();
- // ee.printResultsPlain();
- ee.printResultsLaTeX();
- Files.createFile(new File("enrichment_eval.html"), ee.printHTMLTable());
- FileAppender app = new FileAppender(new SimpleLayout(), "log/enrichmentEvalErrors.log");
- Logger.getRootLogger().setLevel(Level.ERROR);
- Logger.getRootLogger().removeAllAppenders();
- Logger.getRootLogger().addAppender(app);
+ OptionParser parser = new OptionParser();
+ parser.acceptsAll(asList("h", "?", "help"), "Show help.");
+ parser.acceptsAll(asList("e", "endpoint"),
+ "SPARQL endpoint URL to be used.").withRequiredArg()
+ .ofType(URL.class);
+ parser.acceptsAll(asList("g", "graph"),
+ "URI of default graph for queries on SPARQL endpoint.")
+ .withOptionalArg().ofType(URI.class);
+ parser.acceptsAll(asList("c", "classes"),
+ "Run class axiom algorithms")
+ .withOptionalArg().ofType(Boolean.class).defaultsTo(true);
+ parser.acceptsAll(asList("o", "objectProperties"),
+ "Run object property axiom algorithms")
+ .withOptionalArg().ofType(Boolean.class).defaultsTo(true);
+ parser.acceptsAll(asList("d", "dataProperties"),
+ "Run data property axiom algorithms")
+ .withOptionalArg().ofType(Boolean.class).defaultsTo(true);
+ parser.acceptsAll(asList("drop"),
+ "Drop and create tables where data for evaluation is stored.")
+ .withOptionalArg().ofType(Boolean.class).defaultsTo(false);
+
+
+ // parse options and display a message for the user in case of problems
+ OptionSet options = null;
+ try {
+ options = parser.parse(args);
+ } catch (Exception e) {
+ System.out.println("Error: " + e.getMessage()
+ + ". Use -? to get help.");
+ System.exit(0);
+ }
+
+ // print help screen
+ if (options.has("?")) {
+ parser.printHelpOn(System.out);
+ // main script
+ } else {
+ // check that endpoint was specified
+ if (!options.hasArgument("endpoint")) {
+ System.out
+ .println("Please specify a SPARQL endpoint (using the -e option).");
+ System.exit(0);
+ }
+
+ // create SPARQL endpoint object (check that indeed a URL was given)
+ URL endpoint = null;
+ try {
+ endpoint = (URL) options.valueOf("endpoint");
+ } catch (OptionException e) {
+ System.out
+ .println("The specified endpoint appears not to be a proper URL.");
+ System.exit(0);
+ }
+ URI graph = null;
+ try {
+ graph = (URI) options.valueOf("graph");
+ } catch (OptionException e) {
+ System.out
+ .println("The specified graph appears not to be a proper URL.");
+ System.exit(0);
+ }
+
+ LinkedList<String> defaultGraphURIs = new LinkedList<String>();
+ if (graph != null) {
+ defaultGraphURIs.add(graph.toString());
+ }
+
+ SparqlEndpoint se = new SparqlEndpoint(endpoint, defaultGraphURIs,
+ new LinkedList<String>());
+
+ boolean runClassAlgorithms = (Boolean) options.valueOf("classes");
+ boolean runObjectPropertyAlgorithms = (Boolean) options.valueOf("objectProperties");
+ boolean runDataPropertyAlgorithms = (Boolean) options.valueOf("dataProperties");
+
+ boolean dropTables = (Boolean) options.valueOf("drop");
+
+ EnrichmentEvaluation ee = new EnrichmentEvaluation(se);
+ if(dropTables){
+ ee.dropAndCreateTable();
+ }
+ ee.start(runClassAlgorithms, runObjectPropertyAlgorithms, runDataPropertyAlgorithms);
+ // ee.printResultsPlain();
+ ee.printResultsLaTeX();
+ Files.createFile(new File("enrichment_eval.html"),
+ ee.printHTMLTable());
+ FileAppender app = new FileAppender(new SimpleLayout(),
+ "log/enrichmentEvalErrors.log");
+ Logger.getRootLogger().setLevel(Level.ERROR);
+ Logger.getRootLogger().removeAllAppenders();
+ Logger.getRootLogger().addAppender(app);
+ }
}
}
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