bug fix in the authormatch comparator, implementation of tests

dnet-pace-core/src/main/java/eu/dnetlib/pace/common/AbstractPaceFunctions.java

@@ -16,6 +16,8 @@ import org.apache.commons.lang3.StringUtils;
 
 import java.io.IOException;
 import java.io.StringWriter;
+import java.io.UnsupportedEncodingException;
+import java.nio.charset.StandardCharsets;
 import java.text.Normalizer;
 import java.util.*;
 import java.util.function.Function;
@@ -160,6 +162,11 @@ public abstract class AbstractPaceFunctions {
         return Normalizer.normalize(s, Normalizer.Form.NFD);
     }
 
+    public String utf8(final String s) {
+        byte[] bytes = s.getBytes(StandardCharsets.UTF_8);
+        return new String(bytes, StandardCharsets.UTF_8);
+    }
+
     public String unicodeNormalization(final String s) {
 
         Matcher m = hexUnicodePattern.matcher(s);

dnet-pace-core/src/main/java/eu/dnetlib/pace/tree/AuthorsMatch.java

@@ -1,13 +1,13 @@
 package eu.dnetlib.pace.tree;
 
 import com.google.common.collect.Iterables;
-import com.wcohen.ss.JaroWinkler;
 import eu.dnetlib.pace.config.Config;
 import eu.dnetlib.pace.model.Field;
 import eu.dnetlib.pace.model.FieldList;
 import eu.dnetlib.pace.model.Person;
 import eu.dnetlib.pace.tree.support.AbstractComparator;
 import eu.dnetlib.pace.tree.support.ComparatorClass;
+import com.wcohen.ss.AbstractStringDistance;
 
 import java.util.Comparator;
 import java.util.List;
@@ -25,6 +25,7 @@ public class AuthorsMatch extends AbstractComparator {
     private double NAME_THRESHOLD;
     private double FULLNAME_THRESHOLD;
     private String MODE; //full or surname
+    private int common;
 
     public AuthorsMatch(Map<String, String> params){
         super(params, new com.wcohen.ss.JaroWinkler());
@@ -34,6 +35,11 @@ public class AuthorsMatch extends AbstractComparator {
         SURNAME_THRESHOLD = Double.parseDouble(params.getOrDefault("surname_th", "0.95"));
         NAME_THRESHOLD = Double.parseDouble(params.getOrDefault("name_th", "0.95"));
         FULLNAME_THRESHOLD = Double.parseDouble(params.getOrDefault("fullname_th", "0.9"));
+        common = 0;
+    }
+
+    protected AuthorsMatch(double w, AbstractStringDistance ssalgo) {
+        super(w, ssalgo);
     }
 
     @Override
@@ -45,41 +51,85 @@ public class AuthorsMatch extends AbstractComparator {
         List<Person> aList = ((FieldList) a).stringList().stream().map(author -> new Person(author, false)).collect(Collectors.toList());
         List<Person> bList = ((FieldList) b).stringList().stream().map(author -> new Person(author, false)).collect(Collectors.toList());
 
-        int common = 0;
+        common = 0;
+        //compare each element of List1 with each element of List2
         for (Person p1 : aList)
-            for (Person p2 : bList)
+
-                if(MODE.equals("full")) {
+            for (Person p2 : bList) {
-                    if (personComparator(p1, p2))
+
-                        common += 1;
+                //both persons are inaccurate
-                }
+                if (!p1.isAccurate() && !p2.isAccurate()) {
-                else {
+                    //compare just normalized fullnames
-                    if (surnameComparator(p1, p2))
+                    if (ssalgo.score(normalization(p1.getNormalisedFullname()), normalization(p2.getNormalisedFullname())) > FULLNAME_THRESHOLD) {
                         common += 1;
+                        break;
+                    }
                 }
 
-        return (double)common / (aList.size() + bList.size() - common);
+                //one person is inaccurate
+                if (p1.isAccurate() ^ p2.isAccurate()) {
+                    //prepare data
+                    String name = p1.isAccurate()? normalization(p1.getNormalisedFirstName()) : normalization(p2.getNormalisedFirstName());
+                    String surname = p1.isAccurate()? normalization(p2.getNormalisedSurname()) : normalization(p2.getNormalisedSurname());
+
+                    String fullname = p1.isAccurate()? normalization(p2.getNormalisedFullname()) : normalization(p1.getNormalisedFullname());
+
+                    if (fullname.contains(surname)) {
+                        if (MODE.equals("full")) {
+                            if (fullname.contains(name)) {
+                                common += 1;
+                                break;
+                            }
+                        }
+                        else { //MODE equals "surname"
+                            common += 1;
+                            break;
+                        }
+                    }
+                }
+
+                //both persons are accurate
+                if (p1.isAccurate() && p2.isAccurate()) {
+
+                    if (compareSurname(p1, p2)) {
+                        if (MODE.equals("full")) {
+                            if(compareFirstname(p1, p2)) {
+                                common += 1;
+                                break;
+                            }
+                        }
+                        else { //MODE equals "surname"
+                            common += 1;
+                            break;
+                        }
+                    }
+
+                }
+
+            }
+
+        //normalization factor to compute the score
+        int normFactor = aList.size() == bList.size() ? aList.size() : (aList.size() + bList.size() - common);
+
+        return (double)common / normFactor;
     }
 
-    public boolean personComparator(Person p1, Person p2) {
+    public boolean compareSurname(Person p1, Person p2) {
-
+        return ssalgo.score(normalization(p1.getNormalisedSurname()), normalization(p2.getNormalisedSurname())) > SURNAME_THRESHOLD;
-        if(!p1.isAccurate() || !p2.isAccurate())
-            return ssalgo.score(p1.getOriginal(), p2.getOriginal()) > FULLNAME_THRESHOLD;
-
-        if(ssalgo.score(p1.getSurnameString(),p2.getSurnameString()) > SURNAME_THRESHOLD)
-            if(p1.getNameString().length()<=2 || p2.getNameString().length()<=2)
-                return firstLC(p1.getNameString()).equals(firstLC(p2.getNameString()));
-            else
-                return ssalgo.score(p1.getNameString(), p2.getNameString()) > NAME_THRESHOLD;
-        else
-            return false;
     }
 
-    public boolean surnameComparator(Person p1, Person p2) {
+    public boolean compareFirstname(Person p1, Person p2) {
 
-        if(!p1.isAccurate() || !p2.isAccurate())
+        if(p1.getNormalisedFirstName().length()<=2 || p2.getNormalisedFirstName().length()<=2) {
-            return ssalgo.score(p1.getOriginal(), p2.getOriginal()) > FULLNAME_THRESHOLD;
+            if (firstLC(p1.getNormalisedFirstName()).equals(firstLC(p2.getNormalisedFirstName())))
+                return true;
+        }
 
-        return ssalgo.score(p1.getSurnameString(), p2.getSurnameString()) > SURNAME_THRESHOLD;
+        return ssalgo.score(normalization(p1.getNormalisedFirstName()), normalization(p2.getNormalisedFirstName())) > NAME_THRESHOLD;
+    }
+
+    public String normalization(String s) {
+        return normalize(utf8(cleanup(s)));
     }
 
 }

dnet-pace-core/src/main/java/eu/dnetlib/pace/util/BlockProcessorForTesting.java

@@ -36,23 +36,23 @@ public class BlockProcessorForTesting {
             this.dedupConf = dedupConf;
         }
 
-        public void processSortedBlock(final String key, final List<MapDocument> documents, final Reporter context, boolean useTree)  {
+        public void processSortedBlock(final String key, final List<MapDocument> documents, final Reporter context, boolean useTree, boolean noMatch)  {
             if (documents.size() > 1) {
 //            log.info("reducing key: '" + key + "' records: " + q.size());
-                process(prepare(documents), context, useTree);
+                process(prepare(documents), context, useTree, noMatch);
 
             } else {
                 context.incrementCounter(dedupConf.getWf().getEntityType(), "records per hash key = 1", 1);
             }
         }
 
-        public void process(final String key, final Iterable<MapDocument> documents, final Reporter context, boolean useTree)  {
+        public void process(final String key, final Iterable<MapDocument> documents, final Reporter context, boolean useTree, boolean noMatch)  {
 
             final Queue<MapDocument> q = prepare(documents);
 
             if (q.size() > 1) {
 //            log.info("reducing key: '" + key + "' records: " + q.size());
-                process(simplifyQueue(q, key, context), context, useTree);
+                process(simplifyQueue(q, key, context), context, useTree, noMatch);
 
             } else {
                 context.incrementCounter(dedupConf.getWf().getEntityType(), "records per hash key = 1", 1);
@@ -123,7 +123,7 @@ public class BlockProcessorForTesting {
             }
         }
 
-        private void process(final Queue<MapDocument> queue, final Reporter context, boolean useTree)  {
+        private void process(final Queue<MapDocument> queue, final Reporter context, boolean useTree, boolean noMatch)  {
 
             while (!queue.isEmpty()) {
 
@@ -155,18 +155,18 @@ public class BlockProcessorForTesting {
 
                         if (!idCurr.equals(idPivot) && (fieldCurr != null)) {
 
-                            if(!compareInstanceType(pivot, curr, dedupConf)){
+                            //draws no match relations (test purpose)
-                                emitOutput(new TreeProcessor(dedupConf).compare(pivot, curr), idPivot, idCurr, context);
+                            if (noMatch) {
+                                emitOutput(!new TreeProcessor(dedupConf).compare(pivot, curr), idPivot, idCurr, context);
                             }
                             else {
-                                emitOutput(false, idPivot, idCurr, context);
+                                //use the decision tree implementation or the "normal" implementation of the similarity score (valid only for publications)
+                                if(useTree)
+                                    emitOutput(new TreeProcessor(dedupConf).compare(pivot, curr), idPivot, idCurr, context);
+                                else
+                                    emitOutput(publicationCompare(pivot, curr, dedupConf), idPivot, idCurr, context);
                             }
 
-//                            if(useTree)
-//                                emitOutput(new TreeProcessor(dedupConf).compare(pivot, curr), idPivot, idCurr, context);
-//                            else
-//                                emitOutput(publicationCompare(pivot, curr, dedupConf), idPivot, idCurr, context);
-
                         }
                     }
                 }

dnet-pace-core/src/test/java/eu/dnetlib/pace/comparators/ComparatorTest.java

@@ -165,11 +165,6 @@ public class ComparatorTest extends AbstractPaceTest {
 		result = jaroWinkler.distance("Victoria Dataverse", "Windsor Dataverse", conf);
 		System.out.println("result = " + result);
 
-		final Levenstein levenstein = new Levenstein(params);
-
-		result = levenstein.distance("Victoria", "Windsor", conf);
-		System.out.println("result = " + result);
-
 	}
 
 	@Test
@@ -182,6 +177,14 @@ public class ComparatorTest extends AbstractPaceTest {
 		System.out.println("result = " + result);
 	}
 
+	@Test
+	public void levensteinTest() {
+		final Levenstein levenstein = new Levenstein(params);
+
+		double result = levenstein.distance("la bruzzo", "la bruzzo", conf);
+		System.out.println("result = " + result);
+	}
+
 	@Test
 	public void instanceTypeMatchTest() {
 
@@ -238,6 +241,11 @@ public class ComparatorTest extends AbstractPaceTest {
 
 		assertEquals(1.0, result);
 
+		Field e = createFieldList(Arrays.asList("Manghi, Paolo", "Atzori, Claudio"), "authors");
+		result = authorsMatch.compare(a, e, conf);
+
+		assertEquals(0.25, result);
+
 	}
 
 	@Test

dnet-pace-core/src/test/java/eu/dnetlib/pace/util/UtilTest.java

@@ -1,23 +1,35 @@
 package eu.dnetlib.pace.util;
 
+import eu.dnetlib.pace.model.Person;
+import jdk.nashorn.internal.ir.annotations.Ignore;
 import org.junit.jupiter.api.*;
 
 import java.util.HashMap;
 import java.util.Map;
+import static org.junit.jupiter.api.Assertions.assertEquals;
 
 public class UtilTest {
 
-    Map<String, String> params;
+    static Map<String, String> params;
 
     @BeforeAll
-    public void setUp(){
+    public static void setUp(){
-        params = new HashMap<String, String>();
+        params = new HashMap<>();
     }
 
     @Test
+    @Ignore
     public void paceResolverTest() {
         PaceResolver paceResolver = new PaceResolver();
         paceResolver.getComparator("keywordMatch", params);
     }
 
+    @Test
+    public void personTest() {
+        Person p = new Person("j. f. kennedy", false);
+
+        assertEquals("kennedy", p.getSurnameString());
+        assertEquals("j f", p.getNameString());
+    }
+
 }