diff --git a/src/fr/inrialpes/exmo/align/impl/DistanceAlignment.java b/src/fr/inrialpes/exmo/align/impl/DistanceAlignment.java
index 64e735e6288c95188816b7934b6da6204fc96c69..5076c17f770b5d181ab6ea00f3d60e1d51b78b82 100644
--- a/src/fr/inrialpes/exmo/align/impl/DistanceAlignment.java
+++ b/src/fr/inrialpes/exmo/align/impl/DistanceAlignment.java
@@ -1,7 +1,7 @@
/*
* $Id$
*
- * Copyright (C) INRIA Rh�ne-Alpes, 2003-2004
+ * Copyright (C) INRIA Rh�ne-Alpes, 2003-2005
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
@@ -45,7 +45,9 @@ import org.semanticweb.owl.align.AlignmentVisitor;
import org.semanticweb.owl.align.Cell;
import org.semanticweb.owl.align.Relation;
import org.semanticweb.owl.align.Parameters;
+
import fr.inrialpes.exmo.align.impl.Similarity;
+import fr.inrialpes.exmo.align.impl.ConcatenatedIterator;
/**
* Represents an OWL ontology alignment. An ontology comprises a number of
@@ -80,34 +82,72 @@ public class DistanceAlignment extends BasicAlignment
return (1 - getAlignedStrength1(ob));
};
+ /**
+ * Process matching
+ * - create distance data structures,
+ * - compute distance or similarity
+ * - extract alignment
+ **/
+ public void align( Alignment alignment, Parameters params ) throws AlignmentException, OWLException {
+ if ( params.getParameter("type") != null )
+ setType((String)params.getParameter("type"));
+ else setType("**");
+
+ getSimilarity().initialize( (OWLOntology)getOntology1(), (OWLOntology)getOntology2(), alignment );
+ getSimilarity().compute( params );
+ extract( getType(), params );
+ }
+
/**
* Extract the alignment form the Similarity
- * FRom OLA
+ * There are theoretically 16 types of extractors composing the
+ * characteristics
+ * [q]estion mark = ?, one or zero relation
+ * [s]tar = *, one, zero or many relations
+ * [1] = 1, exactly one relation
+ * [p]lus = +, one or many relations
+ * for each place of the relation. Howerver, since it is not possible from a matrics to guarantee that one object will be in at least one relation, this is restricted to the four following types:
+ * ?? (covering 11, 1? and ?1)
+ * ** (covering ++, *+ and +*)
+ * ?* (covering 1*, 1+ and ?+)
+ * *? (covering +?, *1 and +1)
+ */
+ public Alignment extract(String type, Parameters params) throws AlignmentException {
+ double threshold = 0.;
+ if ( params.getParameter("threshold") != null )
+ threshold = ((Double) params.getParameter("threshold")).doubleValue();
+
+ if ( type.equals("?*") || type.equals("1*") || type.equals("?+") || type.equals("1+") ) return extractqs( threshold, params );
+ else if ( type.equals("??") || type.equals("1?") || type.equals("?1") || type.equals("11") ) return extractqs( threshold, params );
+ else if ( type.equals("*?") || type.equals("+?") || type.equals("*1") || type.equals("+1") ) return extractqs( threshold, params );
+ else if ( type.equals("**") || type.equals("+*") || type.equals("*+") || type.equals("++") ) return extractqs( threshold, params );
+ // The else should be an error message
+ else throw new AlignmentException("Unknown alignment type: "+type);
+ }
+
+ /**
+ * Extract the alignment of a ?* type
*/
- public Alignment extract(String type, Parameters param) {
+ public Alignment extractqs( double threshold, Parameters params) {
int i = 0, j = 0;
double max = 0.;
- double threshold = 0.;
boolean found = false;
double val = 0;
- if ( param.getParameter("threshold") != null )
- threshold = ((Double) param.getParameter("threshold")).doubleValue();
-
try {
- for (Iterator it1 = onto1.getObjectProperties().iterator(); it1.hasNext(); ) {
- OWLProperty prop1 = (OWLProperty)it1.next();
+ // Extract for properties
+ ConcatenatedIterator pit1 = new
+ ConcatenatedIterator(onto1.getObjectProperties().iterator(),
+ onto1.getDataProperties().iterator());
+ for ( ; pit1.hasNext(); ) {
+ OWLProperty prop1 = (OWLProperty)pit1.next();
found = false; max = threshold; val = 0;
OWLProperty prop2 = null;
- for (Iterator it2 = onto2.getObjectProperties().iterator(); it2.hasNext(); ) {
- OWLProperty current = (OWLProperty)it2.next();
- val = 1 - sim.getPropertySimilarity(prop1,current);
- if ( val > max) {
- found = true; max = val; prop2 = current;
- }
- }
- for (Iterator it2 = onto2.getDataProperties().iterator(); it2.hasNext();) {
- OWLProperty current = (OWLProperty)it2.next();
+ ConcatenatedIterator pit2 = new
+ ConcatenatedIterator(onto2.getObjectProperties().iterator(),
+ onto2.getDataProperties().iterator());
+ for ( ; pit2.hasNext(); ) {
+ OWLProperty current = (OWLProperty)pit2.next();
val = 1 - sim.getPropertySimilarity(prop1,current);
if ( val > max) {
found = true; max = val; prop2 = current;
@@ -115,84 +155,38 @@ public class DistanceAlignment extends BasicAlignment
}
if ( found ) addAlignCell(prop1,prop2, "=", max);
}
- for (Iterator it1 = onto1.getDataProperties().iterator(); it1.hasNext(); ) {
- OWLProperty prop1 = (OWLProperty)it1.next();
+ // Extract for classes
+ for (Iterator it1 = onto1.getClasses().iterator(); it1.hasNext(); ) {
+ OWLClass class1 = (OWLClass)it1.next();
found = false; max = threshold; val = 0;
- OWLProperty prop2 = null;
- for (Iterator it2 = onto2.getObjectProperties().iterator(); it2.hasNext(); ) {
- OWLProperty current = (OWLProperty)it2.next();
- val = 1 - sim.getPropertySimilarity(prop1,current);
- if ( val > max) {
- found = true; max = val; prop2 = current;
+ OWLClass class2 = null;
+ for (Iterator it2 = onto2.getClasses().iterator(); it2.hasNext(); ) {
+ OWLClass current = (OWLClass)it2.next();
+ val = 1 - sim.getClassSimilarity(class1,current);
+ if (val > max) {
+ found = true; max = val; class2 = current;
}
}
- for (Iterator it2 = onto2.getDataProperties().iterator(); it2.hasNext();) {
- OWLProperty current = (OWLProperty)it2.next();
- val = 1 - sim.getPropertySimilarity(prop1,current);
- if ( val > max) {
- found = true; max = val; prop2 = current;
+ if ( found ) {
+ addAlignCell(class1,class2, "=", max);
+ }
+ }
+ // Extract for properties
+ for (Iterator it1 = onto1.getIndividuals().iterator(); it1.hasNext();) {
+ OWLIndividual ind1 = (OWLIndividual)it1.next();
+ found = false; max = threshold; val = 0;
+ OWLIndividual ind2 = null;
+ for (Iterator it2 = onto2.getIndividuals().iterator(); it2.hasNext(); ) {
+ OWLIndividual current = (OWLIndividual)it2.next();
+ val = 1 - sim.getIndividualSimilarity(ind1,current);
+ if (val > max) {
+ found = true; max = val; ind2 = current;
}
}
- if ( found ) addAlignCell(prop1,prop2, "=", max);
+ if ( found ) addAlignCell(ind1,ind2, "=", max);
}
-
- for (Iterator it1 = onto1.getClasses().iterator(); it1.hasNext(); ) {
- OWLClass class1 = (OWLClass)it1.next();
- found = false; max = threshold; val = 0;
- OWLClass class2 = null;
- for (Iterator it2 = onto2.getClasses().iterator(); it2.hasNext(); ) {
- OWLClass current = (OWLClass)it2.next();
- val = 1 - sim.getClassSimilarity(class1,current);
- if (val > max) {
- found = true; max = val; class2 = current;
- }
- }
- if ( found ) {
- addAlignCell(class1,class2, "=", max);
- }
- }
-
- for (Iterator it1 = onto1.getIndividuals().iterator(); it1.hasNext();) {
- OWLIndividual ind1 = (OWLIndividual)it1.next();
- found = false; max = threshold; val = 0;
- OWLIndividual ind2 = null;
- for (Iterator it2 = onto2.getIndividuals().iterator(); it2.hasNext(); ) {
- OWLIndividual current = (OWLIndividual)it2.next();
- val = 1 - sim.getIndividualSimilarity(ind1,current);
- if (val > max) {
- found = true; max = val; ind2 = current;
- }
- }
- if ( found ) addAlignCell(ind1,ind2, "=", max);
- }
} catch (Exception e2) {e2.printStackTrace();}
return((Alignment)this);
}
- // This mechanism should be parametric!
- // Select the best match
- // There can be many algorithm for these:
- // n:m: get all of those above a threshold
- // 1:1: get the best discard lines and columns and iterate
- // Here we basically implement ?:* because the algorithm
- // picks up the best matching object above threshold for i.
-
- protected void selectBestMatch( int nbobj1, Vector list1, int nbobj2, Vector list2, double[][] matrix, double threshold, Object way) throws AlignmentException {
- if (debug > 0) System.err.print("Storing class alignment\n");
-
- for ( int i=0; i<nbobj1; i++ ){
- boolean found = false;
- int best = 0;
- double max = threshold;
- for ( int j=0; j<nbobj2; j++ ){
- if ( matrix[i][j] < max) {
- found = true;
- best = j;
- max = matrix[i][j];
- }
- }
- if ( found ) { addAlignDistanceCell( (OWLEntity)list1.get(i), (OWLEntity)list2.get(best), "=", max ); }
- }
- }
-
}
diff --git a/src/fr/inrialpes/exmo/align/impl/MatrixMeasure.java b/src/fr/inrialpes/exmo/align/impl/MatrixMeasure.java
index 0b486f96827e5540d135f93bc1a7c9680fee021c..b45746166db9c2992d47bc126bb174a444c08e42 100644
--- a/src/fr/inrialpes/exmo/align/impl/MatrixMeasure.java
+++ b/src/fr/inrialpes/exmo/align/impl/MatrixMeasure.java
@@ -107,6 +107,33 @@ public abstract class MatrixMeasure implements Similarity {
} catch (OWLException e) { e.printStackTrace(); };
}
+ public void compute( Parameters params ){
+ try {
+ // Compute distances on classes
+ for ( Iterator it2 = onto2.getClasses().iterator(); it2.hasNext(); ){
+ OWLClass cl2 = (OWLClass)it2.next();
+ for ( Iterator it1 = onto1.getClasses().iterator(); it1.hasNext(); ){
+ OWLClass cl1 = (OWLClass)it1.next();
+ clmatrix[((Integer)classlist1.get(cl1)).intValue()][((Integer)classlist2.get(cl2)).intValue()] = measure( cl1, cl2 );
+ }
+ }
+ // Compute distances on properties
+ ConcatenatedIterator it2 = new
+ ConcatenatedIterator(onto2.getObjectProperties().iterator(),
+ onto2.getDataProperties().iterator());
+ for ( ; it2.hasNext(); ){
+ OWLProperty pr2 = (OWLProperty)it2.next();
+ ConcatenatedIterator it1 = new
+ ConcatenatedIterator(onto1.getObjectProperties().iterator(),
+ onto1.getDataProperties().iterator());
+ for ( ; it1.hasNext(); ){
+ OWLProperty pr1 = (OWLProperty)it1.next();
+ prmatrix[((Integer)proplist1.get(pr1)).intValue()][((Integer)proplist2.get(pr2)).intValue()] = measure( pr1, pr2 );
+ }
+ }
+ } catch (OWLException e) { e.printStackTrace(); }
+ }
+
public double getIndividualSimilarity( OWLIndividual i1, OWLIndividual i2 ){
// JE: non finished...
int i,j = 0;
diff --git a/src/fr/inrialpes/exmo/align/impl/Similarity.java b/src/fr/inrialpes/exmo/align/impl/Similarity.java
index 4dd066f795d7d4a70dd8d31e60957409b66a5364..29823a2bc84e7205ab8ac446975e7248baae1796 100644
--- a/src/fr/inrialpes/exmo/align/impl/Similarity.java
+++ b/src/fr/inrialpes/exmo/align/impl/Similarity.java
@@ -29,6 +29,7 @@ import org.semanticweb.owl.model.OWLOntology;
import org.semanticweb.owl.model.OWLClass;
import org.semanticweb.owl.model.OWLProperty;
import org.semanticweb.owl.model.OWLIndividual;
+import org.semanticweb.owl.model.OWLException;
import org.semanticweb.owl.align.Parameters;
import org.semanticweb.owl.align.Alignment;
@@ -53,5 +54,9 @@ public interface Similarity
public double getClassSimilarity( OWLClass c1, OWLClass c2 );
public double getPropertySimilarity( OWLProperty p1, OWLProperty p2);
public double getIndividualSimilarity( OWLIndividual i1, OWLIndividual i2 );
+ // New implementation
+ public double measure( OWLClass c1, OWLClass c2 ) throws OWLException;
+ public double measure( OWLProperty p1, OWLProperty p2) throws OWLException;
+ public double measure( OWLIndividual i1, OWLIndividual i2 ) throws OWLException;
}