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resolved conflicts for PR#337

This commit is contained in:
Claudio Atzori 2023-09-06 11:28:46 +02:00
commit da0e9828f7
278 changed files with 32930 additions and 2426 deletions

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@ -52,6 +52,8 @@
</execution>
</executions>
<configuration>
<failOnMultipleScalaVersions>true</failOnMultipleScalaVersions>
<scalaCompatVersion>${scala.binary.version}</scalaCompatVersion>
<scalaVersion>${scala.version}</scalaVersion>
</configuration>
</plugin>
@ -60,6 +62,11 @@
</build>
<dependencies>
<dependency>
<groupId>eu.dnetlib.dhp</groupId>
<artifactId>dhp-pace-core</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
@ -76,11 +83,11 @@
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<artifactId>spark-core_${scala.binary.version}</artifactId>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<artifactId>spark-sql_${scala.binary.version}</artifactId>
</dependency>
<dependency>
@ -142,11 +149,6 @@
<artifactId>okhttp</artifactId>
</dependency>
<dependency>
<groupId>eu.dnetlib</groupId>
<artifactId>dnet-pace-core</artifactId>
</dependency>
<dependency>
<groupId>org.apache.httpcomponents</groupId>
<artifactId>httpclient</artifactId>
@ -159,7 +161,7 @@
<dependency>
<groupId>eu.dnetlib.dhp</groupId>
<artifactId>dhp-schemas</artifactId>
<artifactId>${dhp-schemas.artifact}</artifactId>
</dependency>
<dependency>

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@ -11,25 +11,18 @@ import org.apache.commons.lang3.StringUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FilterFunction;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.*;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.common.HdfsSupport;
import eu.dnetlib.dhp.schema.oaf.Oaf;
import eu.dnetlib.dhp.schema.oaf.OafEntity;
import eu.dnetlib.dhp.schema.common.ModelSupport;
public class DispatchEntitiesSparkJob {
private static final Logger log = LoggerFactory.getLogger(DispatchEntitiesSparkJob.class);
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
@ -54,11 +47,8 @@ public class DispatchEntitiesSparkJob {
String outputPath = parser.get("outputPath");
log.info("outputPath: {}", outputPath);
String graphTableClassName = parser.get("graphTableClassName");
log.info("graphTableClassName: {}", graphTableClassName);
@SuppressWarnings("unchecked")
Class<? extends OafEntity> entityClazz = (Class<? extends OafEntity>) Class.forName(graphTableClassName);
boolean filterInvisible = Boolean.valueOf(parser.get("filterInvisible"));
log.info("filterInvisible: {}", filterInvisible);
SparkConf conf = new SparkConf();
runWithSparkSession(
@ -66,32 +56,43 @@ public class DispatchEntitiesSparkJob {
isSparkSessionManaged,
spark -> {
HdfsSupport.remove(outputPath, spark.sparkContext().hadoopConfiguration());
dispatchEntities(spark, inputPath, entityClazz, outputPath);
dispatchEntities(spark, inputPath, outputPath, filterInvisible);
});
}
private static <T extends Oaf> void dispatchEntities(
private static void dispatchEntities(
SparkSession spark,
String inputPath,
Class<T> clazz,
String outputPath) {
String outputPath,
boolean filterInvisible) {
spark
.read()
.textFile(inputPath)
.filter((FilterFunction<String>) s -> isEntityType(s, clazz))
.map((MapFunction<String, String>) s -> StringUtils.substringAfter(s, "|"), Encoders.STRING())
.map(
(MapFunction<String, T>) value -> OBJECT_MAPPER.readValue(value, clazz),
Encoders.bean(clazz))
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.json(outputPath);
Dataset<String> df = spark.read().textFile(inputPath);
ModelSupport.oafTypes.entrySet().parallelStream().forEach(entry -> {
String entityType = entry.getKey();
Class<?> clazz = entry.getValue();
if (!entityType.equalsIgnoreCase("relation")) {
Dataset<Row> entityDF = spark
.read()
.schema(Encoders.bean(clazz).schema())
.json(
df
.filter((FilterFunction<String>) s -> s.startsWith(clazz.getName()))
.map(
(MapFunction<String, String>) s -> StringUtils.substringAfter(s, "|"),
Encoders.STRING()));
if (filterInvisible) {
entityDF = entityDF.filter("dataInfo.invisible != true");
}
entityDF
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.json(outputPath + "/" + entityType);
}
});
}
private static <T extends Oaf> boolean isEntityType(final String s, final Class<T> clazz) {
return StringUtils.substringBefore(s, "|").equals(clazz.getName());
}
}

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@ -18,9 +18,9 @@
"paramRequired": true
},
{
"paramName": "c",
"paramLongName": "graphTableClassName",
"paramDescription": "the graph entity class name",
"paramName": "fi",
"paramLongName": "filterInvisible",
"paramDescription": "if true filters out invisible entities",
"paramRequired": true
}
]

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@ -0,0 +1,10 @@
package eu.dnetlib.dhp.application.dedup.log
case class DedupLogModel(
tag: String,
configuration: String,
entity: String,
startTS: Long,
endTS: Long,
totalMs: Long
) {}

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@ -0,0 +1,14 @@
package eu.dnetlib.dhp.application.dedup.log
import org.apache.spark.sql.{SaveMode, SparkSession}
class DedupLogWriter(path: String) {
def appendLog(dedupLogModel: DedupLogModel, spark: SparkSession): Unit = {
import spark.implicits._
val df = spark.createDataset[DedupLogModel](data = List(dedupLogModel))
df.write.mode(SaveMode.Append).save(path)
}
}

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@ -8,7 +8,6 @@ import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.List;
import org.junit.jupiter.api.Disabled;
import org.junit.jupiter.api.Test;
import com.fasterxml.jackson.core.JsonProcessingException;
@ -16,8 +15,7 @@ import com.fasterxml.jackson.databind.ObjectMapper;
public class MdStoreClientTest {
@Test
@Disabled
// @Test
public void testMongoCollection() throws IOException {
final MdstoreClient client = new MdstoreClient("mongodb://localhost:27017", "mdstore");

110
dhp-pace-core/pom.xml Normal file
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@ -0,0 +1,110 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>eu.dnetlib.dhp</groupId>
<artifactId>dhp</artifactId>
<version>1.2.5-SNAPSHOT</version>
<relativePath>../pom.xml</relativePath>
</parent>
<groupId>eu.dnetlib.dhp</groupId>
<artifactId>dhp-pace-core</artifactId>
<version>1.2.5-SNAPSHOT</version>
<packaging>jar</packaging>
<build>
<plugins>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>${net.alchim31.maven.version}</version>
<executions>
<execution>
<id>scala-compile-first</id>
<phase>initialize</phase>
<goals>
<goal>add-source</goal>
<goal>compile</goal>
</goals>
</execution>
<execution>
<id>scala-test-compile</id>
<phase>process-test-resources</phase>
<goals>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
<configuration>
<failOnMultipleScalaVersions>true</failOnMultipleScalaVersions>
<scalaCompatVersion>${scala.binary.version}</scalaCompatVersion>
<scalaVersion>${scala.version}</scalaVersion>
</configuration>
</plugin>
</plugins>
</build>
<dependencies>
<dependency>
<groupId>edu.cmu</groupId>
<artifactId>secondstring</artifactId>
</dependency>
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
</dependency>
<dependency>
<groupId>com.google.code.gson</groupId>
<artifactId>gson</artifactId>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
</dependency>
<dependency>
<groupId>commons-io</groupId>
<artifactId>commons-io</artifactId>
</dependency>
<dependency>
<groupId>org.antlr</groupId>
<artifactId>stringtemplate</artifactId>
</dependency>
<dependency>
<groupId>commons-logging</groupId>
<artifactId>commons-logging</artifactId>
</dependency>
<dependency>
<groupId>org.reflections</groupId>
<artifactId>reflections</artifactId>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-math3</artifactId>
</dependency>
<dependency>
<groupId>com.jayway.jsonpath</groupId>
<artifactId>json-path</artifactId>
</dependency>
<dependency>
<groupId>com.ibm.icu</groupId>
<artifactId>icu4j</artifactId>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.binary.version}</artifactId>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.binary.version}</artifactId>
</dependency>
</dependencies>
</project>

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@ -0,0 +1,46 @@
package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import org.apache.commons.lang3.StringUtils;
import eu.dnetlib.pace.common.AbstractPaceFunctions;
import eu.dnetlib.pace.config.Config;
public abstract class AbstractClusteringFunction extends AbstractPaceFunctions implements ClusteringFunction {
protected Map<String, Integer> params;
public AbstractClusteringFunction(final Map<String, Integer> params) {
this.params = params;
}
protected abstract Collection<String> doApply(Config conf, String s);
@Override
public Collection<String> apply(Config conf, List<String> fields) {
return fields
.stream()
.filter(f -> !f.isEmpty())
.map(this::normalize)
.map(s -> filterAllStopWords(s))
.map(s -> doApply(conf, s))
.map(c -> filterBlacklisted(c, ngramBlacklist))
.flatMap(c -> c.stream())
.filter(StringUtils::isNotBlank)
.collect(Collectors.toCollection(HashSet::new));
}
public Map<String, Integer> getParams() {
return params;
}
protected Integer param(String name) {
return params.get(name);
}
}

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@ -0,0 +1,51 @@
package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.Map;
import java.util.Set;
import java.util.StringTokenizer;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("acronyms")
public class Acronyms extends AbstractClusteringFunction {
public Acronyms(Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(Config conf, String s) {
return extractAcronyms(s, param("max"), param("minLen"), param("maxLen"));
}
private Set<String> extractAcronyms(final String s, int maxAcronyms, int minLen, int maxLen) {
final Set<String> acronyms = Sets.newLinkedHashSet();
for (int i = 0; i < maxAcronyms; i++) {
final StringTokenizer st = new StringTokenizer(s);
final StringBuilder sb = new StringBuilder();
while (st.hasMoreTokens()) {
final String token = st.nextToken();
if (sb.length() > maxLen) {
break;
}
if (token.length() > 1 && i < token.length()) {
sb.append(token.charAt(i));
}
}
String acronym = sb.toString();
if (acronym.length() > minLen) {
acronyms.add(acronym);
}
}
return acronyms;
}
}

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@ -0,0 +1,14 @@
package eu.dnetlib.pace.clustering;
import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
@Retention(RetentionPolicy.RUNTIME)
@Target(ElementType.TYPE)
public @interface ClusteringClass {
public String value();
}

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@ -0,0 +1,16 @@
package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
public interface ClusteringFunction {
public Collection<String> apply(Config config, List<String> fields);
public Map<String, Integer> getParams();
}

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@ -0,0 +1,28 @@
package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import com.google.common.collect.Lists;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("immutablefieldvalue")
public class ImmutableFieldValue extends AbstractClusteringFunction {
public ImmutableFieldValue(final Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(final Config conf, final String s) {
final List<String> res = Lists.newArrayList();
res.add(s);
return res;
}
}

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@ -0,0 +1,54 @@
package eu.dnetlib.pace.clustering;
import java.util.*;
import java.util.stream.Collectors;
import org.apache.commons.lang3.StringUtils;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("keywordsclustering")
public class KeywordsClustering extends AbstractClusteringFunction {
public KeywordsClustering(Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(final Config conf, String s) {
// takes city codes and keywords codes without duplicates
Set<String> keywords = getKeywords(s, conf.translationMap(), params.getOrDefault("windowSize", 4));
Set<String> cities = getCities(s, params.getOrDefault("windowSize", 4));
// list of combination to return as result
final Collection<String> combinations = new LinkedHashSet<String>();
for (String keyword : keywordsToCodes(keywords, conf.translationMap())) {
for (String city : citiesToCodes(cities)) {
combinations.add(keyword + "-" + city);
if (combinations.size() >= params.getOrDefault("max", 2)) {
return combinations;
}
}
}
return combinations;
}
@Override
public Collection<String> apply(final Config conf, List<String> fields) {
return fields
.stream()
.filter(f -> !f.isEmpty())
.map(this::cleanup)
.map(this::normalize)
.map(s -> filterAllStopWords(s))
.map(s -> doApply(conf, s))
.map(c -> filterBlacklisted(c, ngramBlacklist))
.flatMap(c -> c.stream())
.filter(StringUtils::isNotBlank)
.collect(Collectors.toCollection(HashSet::new));
}
}

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@ -0,0 +1,79 @@
package eu.dnetlib.pace.clustering;
import java.util.*;
import java.util.stream.Collectors;
import org.apache.commons.lang3.StringUtils;
import com.google.common.collect.Lists;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.model.Person;
@ClusteringClass("lnfi")
public class LastNameFirstInitial extends AbstractClusteringFunction {
private boolean DEFAULT_AGGRESSIVE = true;
public LastNameFirstInitial(final Map<String, Integer> params) {
super(params);
}
@Override
public Collection<String> apply(Config conf, List<String> fields) {
return fields
.stream()
.filter(f -> !f.isEmpty())
.map(this::normalize)
.map(s -> doApply(conf, s))
.map(c -> filterBlacklisted(c, ngramBlacklist))
.flatMap(c -> c.stream())
.filter(StringUtils::isNotBlank)
.collect(Collectors.toCollection(HashSet::new));
}
@Override
protected String normalize(final String s) {
return fixAliases(transliterate(nfd(unicodeNormalization(s))))
// do not compact the regexes in a single expression, would cause StackOverflowError in case of large input
// strings
.replaceAll("[^ \\w]+", "")
.replaceAll("(\\p{InCombiningDiacriticalMarks})+", "")
.replaceAll("(\\p{Punct})+", " ")
.replaceAll("(\\d)+", " ")
.replaceAll("(\\n)+", " ")
.trim();
}
@Override
protected Collection<String> doApply(final Config conf, final String s) {
final List<String> res = Lists.newArrayList();
final boolean aggressive = (Boolean) (getParams().containsKey("aggressive") ? getParams().get("aggressive")
: DEFAULT_AGGRESSIVE);
Person p = new Person(s, aggressive);
if (p.isAccurate()) {
String lastName = p.getNormalisedSurname().toLowerCase();
String firstInitial = p.getNormalisedFirstName().toLowerCase().substring(0, 1);
res.add(firstInitial.concat(lastName));
} else { // is not accurate, meaning it has no defined name and surname
List<String> fullname = Arrays.asList(p.getNormalisedFullname().split(" "));
if (fullname.size() == 1) {
res.add(p.getNormalisedFullname().toLowerCase());
} else if (fullname.size() == 2) {
res.add(fullname.get(0).substring(0, 1).concat(fullname.get(1)).toLowerCase());
res.add(fullname.get(1).substring(0, 1).concat(fullname.get(0)).toLowerCase());
} else {
res.add(fullname.get(0).substring(0, 1).concat(fullname.get(fullname.size() - 1)).toLowerCase());
res.add(fullname.get(fullname.size() - 1).substring(0, 1).concat(fullname.get(0)).toLowerCase());
}
}
return res;
}
}

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@ -0,0 +1,38 @@
package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import org.apache.commons.lang3.StringUtils;
import com.google.common.collect.Lists;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("lowercase")
public class LowercaseClustering extends AbstractClusteringFunction {
public LowercaseClustering(final Map<String, Integer> params) {
super(params);
}
@Override
public Collection<String> apply(Config conf, List<String> fields) {
Collection<String> c = Sets.newLinkedHashSet();
for (String f : fields) {
c.addAll(doApply(conf, f));
}
return c;
}
@Override
protected Collection<String> doApply(final Config conf, final String s) {
if (StringUtils.isBlank(s)) {
return Lists.newArrayList();
}
return Lists.newArrayList(s.toLowerCase().trim());
}
}

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@ -0,0 +1,24 @@
package eu.dnetlib.pace.clustering;
import java.util.Set;
import org.apache.commons.lang3.StringUtils;
import eu.dnetlib.pace.common.AbstractPaceFunctions;
public class NGramUtils extends AbstractPaceFunctions {
static private final NGramUtils NGRAMUTILS = new NGramUtils();
private static final int SIZE = 100;
private static final Set<String> stopwords = AbstractPaceFunctions
.loadFromClasspath("/eu/dnetlib/pace/config/stopwords_en.txt");
public static String cleanupForOrdering(String s) {
return (NGRAMUTILS.filterStopWords(NGRAMUTILS.normalize(s), stopwords) + StringUtils.repeat(" ", SIZE))
.substring(0, SIZE)
.replaceAll(" ", "");
}
}

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@ -0,0 +1,41 @@
package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import com.google.common.collect.Lists;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("ngrampairs")
public class NgramPairs extends Ngrams {
public NgramPairs(Map<String, Integer> params) {
super(params, false);
}
public NgramPairs(Map<String, Integer> params, boolean sorted) {
super(params, sorted);
}
@Override
protected Collection<String> doApply(Config conf, String s) {
return ngramPairs(Lists.newArrayList(getNgrams(s, param("ngramLen"), param("max") * 2, 1, 2)), param("max"));
}
protected Collection<String> ngramPairs(final List<String> ngrams, int maxNgrams) {
Collection<String> res = Lists.newArrayList();
int j = 0;
for (int i = 0; i < ngrams.size() && res.size() < maxNgrams; i++) {
if (++j >= ngrams.size()) {
break;
}
res.add(ngrams.get(i) + ngrams.get(j));
// System.out.println("-- " + concatNgrams);
}
return res;
}
}

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@ -0,0 +1,52 @@
package eu.dnetlib.pace.clustering;
import java.util.*;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("ngrams")
public class Ngrams extends AbstractClusteringFunction {
private final boolean sorted;
public Ngrams(Map<String, Integer> params) {
this(params, false);
}
public Ngrams(Map<String, Integer> params, boolean sorted) {
super(params);
this.sorted = sorted;
}
@Override
protected Collection<String> doApply(Config conf, String s) {
return getNgrams(s, param("ngramLen"), param("max"), param("maxPerToken"), param("minNgramLen"));
}
protected Collection<String> getNgrams(String s, int ngramLen, int max, int maxPerToken, int minNgramLen) {
final Collection<String> ngrams = sorted ? new TreeSet<>() : new LinkedHashSet<String>();
final StringTokenizer st = new StringTokenizer(s);
while (st.hasMoreTokens()) {
final String token = st.nextToken();
if (!token.isEmpty()) {
for (int i = 0; i < maxPerToken && ngramLen + i <= token.length(); i++) {
String ngram = token.substring(i, Math.min(ngramLen + i, token.length())).trim();
if (ngram.length() >= minNgramLen) {
ngrams.add(ngram);
if (ngrams.size() >= max) {
return ngrams;
}
}
}
}
}
// System.out.println(ngrams + " n: " + ngrams.size());
return ngrams;
}
}

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@ -0,0 +1,84 @@
package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import java.util.Set;
import org.apache.commons.lang3.StringUtils;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.common.AbstractPaceFunctions;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.model.Person;
@ClusteringClass("personClustering")
public class PersonClustering extends AbstractPaceFunctions implements ClusteringFunction {
private Map<String, Integer> params;
private static final int MAX_TOKENS = 5;
public PersonClustering(final Map<String, Integer> params) {
this.params = params;
}
@Override
public Collection<String> apply(final Config conf, final List<String> fields) {
final Set<String> hashes = Sets.newHashSet();
for (final String f : fields) {
final Person person = new Person(f, false);
if (StringUtils.isNotBlank(person.getNormalisedFirstName())
&& StringUtils.isNotBlank(person.getNormalisedSurname())) {
hashes.add(firstLC(person.getNormalisedFirstName()) + person.getNormalisedSurname().toLowerCase());
} else {
for (final String token1 : tokens(f, MAX_TOKENS)) {
for (final String token2 : tokens(f, MAX_TOKENS)) {
if (!token1.equals(token2)) {
hashes.add(firstLC(token1) + token2);
}
}
}
}
}
return hashes;
}
// @Override
// public Collection<String> apply(final List<Field> fields) {
// final Set<String> hashes = Sets.newHashSet();
//
// for (final Field f : fields) {
//
// final GTAuthor gta = GTAuthor.fromOafJson(f.stringValue());
//
// final Author a = gta.getAuthor();
//
// if (StringUtils.isNotBlank(a.getFirstname()) && StringUtils.isNotBlank(a.getSecondnames())) {
// hashes.add(firstLC(a.getFirstname()) + a.getSecondnames().toLowerCase());
// } else {
// for (final String token1 : tokens(f.stringValue(), MAX_TOKENS)) {
// for (final String token2 : tokens(f.stringValue(), MAX_TOKENS)) {
// if (!token1.equals(token2)) {
// hashes.add(firstLC(token1) + token2);
// }
// }
// }
// }
// }
//
// return hashes;
// }
@Override
public Map<String, Integer> getParams() {
return params;
}
}

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@ -0,0 +1,34 @@
package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import com.google.common.collect.Lists;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.model.Person;
@ClusteringClass("personHash")
public class PersonHash extends AbstractClusteringFunction {
private boolean DEFAULT_AGGRESSIVE = false;
public PersonHash(final Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(final Config conf, final String s) {
final List<String> res = Lists.newArrayList();
final boolean aggressive = (Boolean) (getParams().containsKey("aggressive") ? getParams().get("aggressive")
: DEFAULT_AGGRESSIVE);
res.add(new Person(s, aggressive).hash());
return res;
}
}

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package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
public class RandomClusteringFunction extends AbstractClusteringFunction {
public RandomClusteringFunction(Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(final Config conf, String s) {
return null;
}
}

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package eu.dnetlib.pace.clustering;
import java.util.*;
import com.google.common.base.Joiner;
import com.google.common.base.Splitter;
import com.google.common.collect.Lists;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("sortedngrampairs")
public class SortedNgramPairs extends NgramPairs {
public SortedNgramPairs(Map<String, Integer> params) {
super(params, false);
}
@Override
protected Collection<String> doApply(Config conf, String s) {
final List<String> tokens = Lists.newArrayList(Splitter.on(" ").omitEmptyStrings().trimResults().split(s));
Collections.sort(tokens);
return ngramPairs(
Lists.newArrayList(getNgrams(Joiner.on(" ").join(tokens), param("ngramLen"), param("max") * 2, 1, 2)),
param("max"));
}
}

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package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import org.apache.commons.lang3.RandomStringUtils;
import org.apache.commons.lang3.StringUtils;
import com.google.common.collect.Lists;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("spacetrimmingfieldvalue")
public class SpaceTrimmingFieldValue extends AbstractClusteringFunction {
public SpaceTrimmingFieldValue(final Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(final Config conf, final String s) {
final List<String> res = Lists.newArrayList();
res
.add(
StringUtils.isBlank(s) ? RandomStringUtils.random(getParams().get("randomLength"))
: s.toLowerCase().replaceAll("\\s+", ""));
return res;
}
}

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package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.Map;
import java.util.Set;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("suffixprefix")
public class SuffixPrefix extends AbstractClusteringFunction {
public SuffixPrefix(Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(Config conf, String s) {
return suffixPrefix(s, param("len"), param("max"));
}
private Collection<String> suffixPrefix(String s, int len, int max) {
final Set<String> bigrams = Sets.newLinkedHashSet();
int i = 0;
while (++i < s.length() && bigrams.size() < max) {
int j = s.indexOf(" ", i);
int offset = j + len + 1 < s.length() ? j + len + 1 : s.length();
if (j - len > 0) {
String bigram = s.substring(j - len, offset).replaceAll(" ", "").trim();
if (bigram.length() >= 4) {
bigrams.add(bigram);
}
}
}
return bigrams;
}
}

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package eu.dnetlib.pace.clustering;
import java.net.MalformedURLException;
import java.net.URL;
import java.util.Collection;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import eu.dnetlib.pace.common.AbstractPaceFunctions;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("urlclustering")
public class UrlClustering extends AbstractPaceFunctions implements ClusteringFunction {
protected Map<String, Integer> params;
public UrlClustering(final Map<String, Integer> params) {
this.params = params;
}
@Override
public Collection<String> apply(final Config conf, List<String> fields) {
try {
return fields
.stream()
.filter(f -> !f.isEmpty())
.map(this::asUrl)
.map(URL::getHost)
.collect(Collectors.toCollection(HashSet::new));
} catch (IllegalStateException e) {
return new HashSet<>();
}
}
@Override
public Map<String, Integer> getParams() {
return null;
}
private URL asUrl(String value) {
try {
return new URL(value);
} catch (MalformedURLException e) {
// should not happen as checked by pace typing
throw new IllegalStateException("invalid URL: " + value);
}
}
}

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package eu.dnetlib.pace.clustering;
import java.util.*;
import java.util.stream.Collectors;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("wordsStatsSuffixPrefixChain")
public class WordsStatsSuffixPrefixChain extends AbstractClusteringFunction {
public WordsStatsSuffixPrefixChain(Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(Config conf, String s) {
return suffixPrefixChain(s, param("mod"));
}
private Collection<String> suffixPrefixChain(String s, int mod) {
// create the list of words from the string (remove short words)
List<String> wordsList = Arrays
.stream(s.split(" "))
.filter(si -> si.length() > 3)
.collect(Collectors.toList());
final int words = wordsList.size();
final int letters = s.length();
// create the prefix: number of words + number of letters/mod
String prefix = words + "-" + letters / mod + "-";
return doSuffixPrefixChain(wordsList, prefix);
}
private Collection<String> doSuffixPrefixChain(List<String> wordsList, String prefix) {
Set<String> set = Sets.newLinkedHashSet();
switch (wordsList.size()) {
case 0:
case 1:
break;
case 2:
set
.add(
prefix +
suffix(wordsList.get(0), 3) +
prefix(wordsList.get(1), 3));
set
.add(
prefix +
prefix(wordsList.get(0), 3) +
suffix(wordsList.get(1), 3));
break;
default:
set
.add(
prefix +
suffix(wordsList.get(0), 3) +
prefix(wordsList.get(1), 3) +
suffix(wordsList.get(2), 3));
set
.add(
prefix +
prefix(wordsList.get(0), 3) +
suffix(wordsList.get(1), 3) +
prefix(wordsList.get(2), 3));
break;
}
return set;
}
private String suffix(String s, int len) {
return s.substring(s.length() - len);
}
private String prefix(String s, int len) {
return s.substring(0, len);
}
}

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package eu.dnetlib.pace.clustering;
import java.util.Collection;
import java.util.Map;
import java.util.Set;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.config.Config;
@ClusteringClass("wordssuffixprefix")
public class WordsSuffixPrefix extends AbstractClusteringFunction {
public WordsSuffixPrefix(Map<String, Integer> params) {
super(params);
}
@Override
protected Collection<String> doApply(Config conf, String s) {
return suffixPrefix(s, param("len"), param("max"));
}
private Collection<String> suffixPrefix(String s, int len, int max) {
final int words = s.split(" ").length;
// adjust the token length according to the number of words
switch (words) {
case 1:
return Sets.newLinkedHashSet();
case 2:
return doSuffixPrefix(s, len + 2, max, words);
case 3:
return doSuffixPrefix(s, len + 1, max, words);
default:
return doSuffixPrefix(s, len, max, words);
}
}
private Collection<String> doSuffixPrefix(String s, int len, int max, int words) {
final Set<String> bigrams = Sets.newLinkedHashSet();
int i = 0;
while (++i < s.length() && bigrams.size() < max) {
int j = s.indexOf(" ", i);
int offset = j + len + 1 < s.length() ? j + len + 1 : s.length();
if (j - len > 0) {
String bigram = s.substring(j - len, offset).replaceAll(" ", "").trim();
if (bigram.length() >= 4) {
bigrams.add(words + bigram);
}
}
}
return bigrams;
}
}

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package eu.dnetlib.pace.common;
import java.io.IOException;
import java.io.StringWriter;
import java.nio.charset.StandardCharsets;
import java.text.Normalizer;
import java.util.*;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
import java.util.stream.Collectors;
import org.apache.commons.io.IOUtils;
import org.apache.commons.lang3.StringUtils;
import com.google.common.base.Joiner;
import com.google.common.base.Splitter;
import com.google.common.collect.Iterables;
import com.google.common.collect.Lists;
import com.google.common.collect.Sets;
import com.ibm.icu.text.Transliterator;
import eu.dnetlib.pace.clustering.NGramUtils;
/**
* Set of common functions for the framework
*
* @author claudio
*/
public abstract class AbstractPaceFunctions {
// city map to be used when translating the city names into codes
private static Map<String, String> cityMap = AbstractPaceFunctions
.loadMapFromClasspath("/eu/dnetlib/pace/config/city_map.csv");
// list of stopwords in different languages
protected static Set<String> stopwords_gr = loadFromClasspath("/eu/dnetlib/pace/config/stopwords_gr.txt");
protected static Set<String> stopwords_en = loadFromClasspath("/eu/dnetlib/pace/config/stopwords_en.txt");
protected static Set<String> stopwords_de = loadFromClasspath("/eu/dnetlib/pace/config/stopwords_de.txt");
protected static Set<String> stopwords_es = loadFromClasspath("/eu/dnetlib/pace/config/stopwords_es.txt");
protected static Set<String> stopwords_fr = loadFromClasspath("/eu/dnetlib/pace/config/stopwords_fr.txt");
protected static Set<String> stopwords_it = loadFromClasspath("/eu/dnetlib/pace/config/stopwords_it.txt");
protected static Set<String> stopwords_pt = loadFromClasspath("/eu/dnetlib/pace/config/stopwords_pt.txt");
// transliterator
protected static Transliterator transliterator = Transliterator.getInstance("Any-Eng");
// blacklist of ngrams: to avoid generic keys
protected static Set<String> ngramBlacklist = loadFromClasspath("/eu/dnetlib/pace/config/ngram_blacklist.txt");
// html regex for normalization
public static final Pattern HTML_REGEX = Pattern.compile("<[^>]*>");
private static final String alpha = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789 ";
private static final String aliases_from = "⁰¹²³⁴⁵⁶⁷⁸⁹⁺⁻⁼⁽⁾ⁿ₀₁₂₃₄₅₆₇₈₉₊₋₌₍₎àáâäæãåāèéêëēėęəîïíīįìôöòóœøōõûüùúūßśšłžźżçćčñń";
private static final String aliases_to = "0123456789+-=()n0123456789+-=()aaaaaaaaeeeeeeeeiiiiiioooooooouuuuussslzzzcccnn";
// doi prefix for normalization
public static final Pattern DOI_PREFIX = Pattern.compile("(https?:\\/\\/dx\\.doi\\.org\\/)|(doi:)");
private static Pattern numberPattern = Pattern.compile("-?\\d+(\\.\\d+)?");
private static Pattern hexUnicodePattern = Pattern.compile("\\\\u(\\p{XDigit}{4})");
protected String concat(final List<String> l) {
return Joiner.on(" ").skipNulls().join(l);
}
protected String cleanup(final String s) {
final String s1 = HTML_REGEX.matcher(s).replaceAll("");
final String s2 = unicodeNormalization(s1.toLowerCase());
final String s3 = nfd(s2);
final String s4 = fixXML(s3);
final String s5 = s4.replaceAll("([0-9]+)", " $1 ");
final String s6 = transliterate(s5);
final String s7 = fixAliases(s6);
final String s8 = s7.replaceAll("[^\\p{ASCII}]", "");
final String s9 = s8.replaceAll("[\\p{Punct}]", " ");
final String s10 = s9.replaceAll("\\n", " ");
final String s11 = s10.replaceAll("(?m)\\s+", " ");
final String s12 = s11.trim();
return s12;
}
protected String fixXML(final String a) {
return a
.replaceAll("&ndash;", " ")
.replaceAll("&amp;", " ")
.replaceAll("&quot;", " ")
.replaceAll("&minus;", " ");
}
protected boolean checkNumbers(final String a, final String b) {
final String numbersA = getNumbers(a);
final String numbersB = getNumbers(b);
final String romansA = getRomans(a);
final String romansB = getRomans(b);
return !numbersA.equals(numbersB) || !romansA.equals(romansB);
}
protected String getRomans(final String s) {
final StringBuilder sb = new StringBuilder();
for (final String t : s.split(" ")) {
sb.append(isRoman(t) ? t : "");
}
return sb.toString();
}
protected boolean isRoman(final String s) {
return s
.replaceAll("^M{0,4}(CM|CD|D?C{0,3})(XC|XL|L?X{0,3})(IX|IV|V?I{0,3})$", "qwertyuiop")
.equals("qwertyuiop");
}
protected String getNumbers(final String s) {
final StringBuilder sb = new StringBuilder();
for (final String t : s.split(" ")) {
sb.append(isNumber(t) ? t : "");
}
return sb.toString();
}
public boolean isNumber(String strNum) {
if (strNum == null) {
return false;
}
return numberPattern.matcher(strNum).matches();
}
protected static String fixAliases(final String s) {
final StringBuilder sb = new StringBuilder();
s.chars().forEach(ch -> {
final int i = StringUtils.indexOf(aliases_from, ch);
sb.append(i >= 0 ? aliases_to.charAt(i) : (char) ch);
});
return sb.toString();
}
protected static String transliterate(final String s) {
try {
return transliterator.transliterate(s);
} catch (Exception e) {
return s;
}
}
protected String removeSymbols(final String s) {
final StringBuilder sb = new StringBuilder();
s.chars().forEach(ch -> {
sb.append(StringUtils.contains(alpha, ch) ? (char) ch : ' ');
});
return sb.toString().replaceAll("\\s+", " ");
}
protected boolean notNull(final String s) {
return s != null;
}
protected String normalize(final String s) {
return fixAliases(transliterate(nfd(unicodeNormalization(s))))
.toLowerCase()
// do not compact the regexes in a single expression, would cause StackOverflowError in case of large input
// strings
.replaceAll("[^ \\w]+", "")
.replaceAll("(\\p{InCombiningDiacriticalMarks})+", "")
.replaceAll("(\\p{Punct})+", " ")
.replaceAll("(\\d)+", " ")
.replaceAll("(\\n)+", " ")
.trim();
}
public String nfd(final String s) {
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);
StringBuffer buf = new StringBuffer(s.length());
while (m.find()) {
String ch = String.valueOf((char) Integer.parseInt(m.group(1), 16));
m.appendReplacement(buf, Matcher.quoteReplacement(ch));
}
m.appendTail(buf);
return buf.toString();
}
protected String filterStopWords(final String s, final Set<String> stopwords) {
final StringTokenizer st = new StringTokenizer(s);
final StringBuilder sb = new StringBuilder();
while (st.hasMoreTokens()) {
final String token = st.nextToken();
if (!stopwords.contains(token)) {
sb.append(token);
sb.append(" ");
}
}
return sb.toString().trim();
}
public String filterAllStopWords(String s) {
s = filterStopWords(s, stopwords_en);
s = filterStopWords(s, stopwords_de);
s = filterStopWords(s, stopwords_it);
s = filterStopWords(s, stopwords_fr);
s = filterStopWords(s, stopwords_pt);
s = filterStopWords(s, stopwords_es);
s = filterStopWords(s, stopwords_gr);
return s;
}
protected Collection<String> filterBlacklisted(final Collection<String> set, final Set<String> ngramBlacklist) {
final Set<String> newset = Sets.newLinkedHashSet();
for (final String s : set) {
if (!ngramBlacklist.contains(s)) {
newset.add(s);
}
}
return newset;
}
public static Set<String> loadFromClasspath(final String classpath) {
Transliterator transliterator = Transliterator.getInstance("Any-Eng");
final Set<String> h = Sets.newHashSet();
try {
for (final String s : IOUtils
.readLines(NGramUtils.class.getResourceAsStream(classpath), StandardCharsets.UTF_8)) {
h.add(fixAliases(transliterator.transliterate(s))); // transliteration of the stopwords
}
} catch (final Throwable e) {
return Sets.newHashSet();
}
return h;
}
public static Map<String, String> loadMapFromClasspath(final String classpath) {
Transliterator transliterator = Transliterator.getInstance("Any-Eng");
final Map<String, String> m = new HashMap<>();
try {
for (final String s : IOUtils
.readLines(AbstractPaceFunctions.class.getResourceAsStream(classpath), StandardCharsets.UTF_8)) {
// string is like this: code;word1;word2;word3
String[] line = s.split(";");
String value = line[0];
for (int i = 1; i < line.length; i++) {
m.put(fixAliases(transliterator.transliterate(line[i].toLowerCase())), value);
}
}
} catch (final Throwable e) {
return new HashMap<>();
}
return m;
}
public String removeKeywords(String s, Set<String> keywords) {
s = " " + s + " ";
for (String k : keywords) {
s = s.replaceAll(k.toLowerCase(), "");
}
return s.trim();
}
public double commonElementsPercentage(Set<String> s1, Set<String> s2) {
double longer = Math.max(s1.size(), s2.size());
return (double) s1.stream().filter(s2::contains).count() / longer;
}
// convert the set of keywords to codes
public Set<String> toCodes(Set<String> keywords, Map<String, String> translationMap) {
return keywords.stream().map(s -> translationMap.get(s)).collect(Collectors.toSet());
}
public Set<String> keywordsToCodes(Set<String> keywords, Map<String, String> translationMap) {
return toCodes(keywords, translationMap);
}
public Set<String> citiesToCodes(Set<String> keywords) {
return toCodes(keywords, cityMap);
}
protected String firstLC(final String s) {
return StringUtils.substring(s, 0, 1).toLowerCase();
}
protected Iterable<String> tokens(final String s, final int maxTokens) {
return Iterables.limit(Splitter.on(" ").omitEmptyStrings().trimResults().split(s), maxTokens);
}
public String normalizePid(String pid) {
return DOI_PREFIX.matcher(pid.toLowerCase()).replaceAll("");
}
// get the list of keywords into the input string
public Set<String> getKeywords(String s1, Map<String, String> translationMap, int windowSize) {
String s = s1;
List<String> tokens = Arrays.asList(s.toLowerCase().split(" "));
Set<String> codes = new HashSet<>();
if (tokens.size() < windowSize)
windowSize = tokens.size();
int length = windowSize;
while (length != 0) {
for (int i = 0; i <= tokens.size() - length; i++) {
String candidate = concat(tokens.subList(i, i + length));
if (translationMap.containsKey(candidate)) {
codes.add(candidate);
s = s.replace(candidate, "").trim();
}
}
tokens = Arrays.asList(s.split(" "));
length -= 1;
}
return codes;
}
public Set<String> getCities(String s1, int windowSize) {
return getKeywords(s1, cityMap, windowSize);
}
public static <T> String readFromClasspath(final String filename, final Class<T> clazz) {
final StringWriter sw = new StringWriter();
try {
IOUtils.copy(clazz.getResourceAsStream(filename), sw, StandardCharsets.UTF_8);
return sw.toString();
} catch (final IOException e) {
throw new RuntimeException("cannot load resource from classpath: " + filename);
}
}
}

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package eu.dnetlib.pace.config;
import java.util.List;
import java.util.Map;
import java.util.function.Predicate;
import eu.dnetlib.pace.model.ClusteringDef;
import eu.dnetlib.pace.model.FieldDef;
import eu.dnetlib.pace.tree.support.TreeNodeDef;
/**
* Interface for PACE configuration bean.
*
* @author claudio
*/
public interface Config {
/**
* Field configuration definitions.
*
* @return the list of definitions
*/
public List<FieldDef> model();
/**
* Decision Tree definition
*
* @return the map representing the decision tree
*/
public Map<String, TreeNodeDef> decisionTree();
/**
* Clusterings.
*
* @return the list
*/
public List<ClusteringDef> clusterings();
/**
* Blacklists.
*
* @return the map
*/
public Map<String, Predicate<String>> blacklists();
/**
* Translation map.
*
* @return the map
* */
public Map<String, String> translationMap();
}

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package eu.dnetlib.pace.config;
import java.io.IOException;
import java.io.Serializable;
import java.nio.charset.StandardCharsets;
import java.util.AbstractMap;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.function.Predicate;
import java.util.regex.Pattern;
import java.util.regex.PatternSyntaxException;
import java.util.stream.Collectors;
import org.antlr.stringtemplate.StringTemplate;
import org.apache.commons.io.IOUtils;
import org.apache.commons.lang3.StringUtils;
import com.fasterxml.jackson.annotation.JsonIgnore;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.google.common.collect.Maps;
import eu.dnetlib.pace.model.ClusteringDef;
import eu.dnetlib.pace.model.FieldDef;
import eu.dnetlib.pace.tree.support.TreeNodeDef;
import eu.dnetlib.pace.util.PaceException;
public class DedupConfig implements Config, Serializable {
private static String CONFIG_TEMPLATE = "dedupConfig.st";
private PaceConfig pace;
private WfConfig wf;
@JsonIgnore
private Map<String, Predicate<String>> blacklists;
private static Map<String, String> defaults = Maps.newHashMap();
static {
defaults.put("dedupRun", "001");
defaults.put("entityType", "result");
defaults.put("subEntityType", "resulttype");
defaults.put("subEntityValue", "publication");
defaults.put("orderField", "title");
defaults.put("queueMaxSize", "2000");
defaults.put("groupMaxSize", "10");
defaults.put("slidingWindowSize", "200");
defaults.put("rootBuilder", "result");
defaults.put("includeChildren", "true");
defaults.put("maxIterations", "20");
defaults.put("idPath", "$.id");
}
public DedupConfig() {
}
public static DedupConfig load(final String json) {
final DedupConfig config;
try {
config = new ObjectMapper().readValue(json, DedupConfig.class);
config.getPace().initModel();
config.getPace().initTranslationMap();
config.blacklists = config
.getPace()
.getBlacklists()
.entrySet()
.stream()
.map(
e -> new AbstractMap.SimpleEntry<String, List<Pattern>>(e.getKey(),
e
.getValue()
.stream()
.filter(s -> !StringUtils.isBlank(s))
.map(Pattern::compile)
.collect(Collectors.toList())))
.collect(
Collectors
.toMap(
e -> e.getKey(),
e -> (Predicate<String> & Serializable) s -> e
.getValue()
.stream()
.filter(p -> p.matcher(s).matches())
.findFirst()
.isPresent()))
;
return config;
} catch (IOException | PatternSyntaxException e) {
throw new PaceException("Error in parsing configuration json", e);
}
}
public static DedupConfig loadDefault() throws IOException {
return loadDefault(new HashMap<String, String>());
}
public static DedupConfig loadDefault(final Map<String, String> params) throws IOException {
final StringTemplate template = new StringTemplate(new DedupConfig().readFromClasspath(CONFIG_TEMPLATE));
for (final Entry<String, String> e : defaults.entrySet()) {
template.setAttribute(e.getKey(), e.getValue());
}
for (final Entry<String, String> e : params.entrySet()) {
if (template.getAttribute(e.getKey()) != null) {
template.getAttributes().computeIfPresent(e.getKey(), (o, o2) -> e.getValue());
} else {
template.setAttribute(e.getKey(), e.getValue());
}
}
final String json = template.toString();
return load(json);
}
private String readFromClasspath(final String resource) throws IOException {
return IOUtils.toString(getClass().getResource(resource), StandardCharsets.UTF_8);
}
public PaceConfig getPace() {
return pace;
}
public void setPace(final PaceConfig pace) {
this.pace = pace;
}
public WfConfig getWf() {
return wf;
}
public void setWf(final WfConfig wf) {
this.wf = wf;
}
@Override
public String toString() {
try {
return new ObjectMapper().writeValueAsString(this);
} catch (IOException e) {
throw new PaceException("unable to serialise configuration", e);
}
}
@Override
public Map<String, TreeNodeDef> decisionTree() {
return getPace().getDecisionTree();
}
@Override
public List<FieldDef> model() {
return getPace().getModel();
}
@Override
public List<ClusteringDef> clusterings() {
return getPace().getClustering();
}
@Override
public Map<String, Predicate<String>> blacklists() {
return blacklists;
}
@Override
public Map<String, String> translationMap() {
return getPace().translationMap();
}
}

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package eu.dnetlib.pace.config;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonIgnore;
import com.google.common.collect.Maps;
import com.ibm.icu.text.Transliterator;
import eu.dnetlib.pace.common.AbstractPaceFunctions;
import eu.dnetlib.pace.model.ClusteringDef;
import eu.dnetlib.pace.model.FieldDef;
import eu.dnetlib.pace.tree.support.TreeNodeDef;
import eu.dnetlib.pace.util.PaceResolver;
public class PaceConfig extends AbstractPaceFunctions implements Serializable {
private List<FieldDef> model;
private List<ClusteringDef> clustering;
private Map<String, TreeNodeDef> decisionTree;
private Map<String, List<String>> blacklists;
private Map<String, List<String>> synonyms;
@JsonIgnore
private Map<String, String> translationMap;
public Map<String, FieldDef> getModelMap() {
return modelMap;
}
@JsonIgnore
private Map<String, FieldDef> modelMap;
@JsonIgnore
public static PaceResolver resolver = new PaceResolver();
public PaceConfig() {
}
public void initModel() {
modelMap = Maps.newHashMap();
for (FieldDef fd : getModel()) {
modelMap.put(fd.getName(), fd);
}
}
public void initTranslationMap() {
translationMap = Maps.newHashMap();
Transliterator transliterator = Transliterator.getInstance("Any-Eng");
for (String key : synonyms.keySet()) {
for (String term : synonyms.get(key)) {
translationMap
.put(
fixAliases(transliterator.transliterate(term.toLowerCase())),
key);
}
}
}
public Map<String, String> translationMap() {
return translationMap;
}
public List<FieldDef> getModel() {
return model;
}
public void setModel(final List<FieldDef> model) {
this.model = model;
}
public List<ClusteringDef> getClustering() {
return clustering;
}
public void setClustering(final List<ClusteringDef> clustering) {
this.clustering = clustering;
}
public Map<String, TreeNodeDef> getDecisionTree() {
return decisionTree;
}
public void setDecisionTree(Map<String, TreeNodeDef> decisionTree) {
this.decisionTree = decisionTree;
}
public Map<String, List<String>> getBlacklists() {
return blacklists;
}
public void setBlacklists(final Map<String, List<String>> blacklists) {
this.blacklists = blacklists;
}
public Map<String, List<String>> getSynonyms() {
return synonyms;
}
public void setSynonyms(Map<String, List<String>> synonyms) {
this.synonyms = synonyms;
}
}

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package eu.dnetlib.pace.config;
public enum Type {
String, Int, List, JSON, URL, StringConcat, DoubleArray
}

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package eu.dnetlib.pace.config;
import java.io.IOException;
import java.io.Serializable;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import org.apache.commons.lang3.StringUtils;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.google.common.collect.Lists;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.util.PaceException;
public class WfConfig implements Serializable {
/**
* Entity type.
*/
private String entityType = "";
/**
* Sub-Entity type refers to one of fields declared in the model. See eu.dnetlib.pace.config.PaceConfig.modelMap
*/
private String subEntityType = "";
/**
* Sub-Entity value declares a value for subTypes to be considered.
*/
private String subEntityValue = "";
/**
* Field name used to sort the values in the reducer phase.
*/
private String orderField = "";
/**
* Column Families involved in the relations redirection.
*/
private List<String> rootBuilder = Lists.newArrayList();
/**
* Set of datasource namespace prefixes that won't be deduplicated.
*/
private Set<String> skipList = Sets.newHashSet();
/**
* Subprefix used to build the root id, allows multiple dedup runs.
*/
private String dedupRun = "";
/**
* Similarity threshold.
*/
private double threshold = 0;
/** The queue max size. */
private int queueMaxSize = 2000;
/** The group max size. */
private int groupMaxSize;
/** The sliding window size. */
private int slidingWindowSize;
/** The configuration id. */
private String configurationId;
/** The include children. */
private boolean includeChildren;
/** Default maximum number of allowed children. */
private final static int MAX_CHILDREN = 10;
/** Maximum number of allowed children. */
private int maxChildren = MAX_CHILDREN;
/** Default maximum number of iterations. */
private final static int MAX_ITERATIONS = 20;
/** Maximum number of iterations */
private int maxIterations = MAX_ITERATIONS;
/** The Jquery path to retrieve the identifier */
private String idPath = "$.id";
public WfConfig() {
}
/**
* Instantiates a new dedup config.
*
* @param entityType
* the entity type
* @param orderField
* the order field
* @param rootBuilder
* the root builder families
* @param dedupRun
* the dedup run
* @param skipList
* the skip list
* @param queueMaxSize
* the queue max size
* @param groupMaxSize
* the group max size
* @param slidingWindowSize
* the sliding window size
* @param includeChildren
* allows the children to be included in the representative records or not.
* @param maxIterations
* the maximum number of iterations
* @param idPath
* the path for the id of the entity
*/
public WfConfig(final String entityType, final String orderField, final List<String> rootBuilder,
final String dedupRun,
final Set<String> skipList, final int queueMaxSize, final int groupMaxSize, final int slidingWindowSize,
final boolean includeChildren, final int maxIterations, final String idPath) {
super();
this.entityType = entityType;
this.orderField = orderField;
this.rootBuilder = rootBuilder;
this.dedupRun = cleanupStringNumber(dedupRun);
this.skipList = skipList;
this.queueMaxSize = queueMaxSize;
this.groupMaxSize = groupMaxSize;
this.slidingWindowSize = slidingWindowSize;
this.includeChildren = includeChildren;
this.maxIterations = maxIterations;
this.idPath = idPath;
}
/**
* Cleanup string number.
*
* @param s
* the s
* @return the string
*/
private String cleanupStringNumber(final String s) {
return s.contains("'") ? s.replaceAll("'", "") : s;
}
public boolean hasSubType() {
return StringUtils.isNotBlank(getSubEntityType()) && StringUtils.isNotBlank(getSubEntityValue());
}
public String getEntityType() {
return entityType;
}
public void setEntityType(final String entityType) {
this.entityType = entityType;
}
public String getSubEntityType() {
return subEntityType;
}
public void setSubEntityType(final String subEntityType) {
this.subEntityType = subEntityType;
}
public String getSubEntityValue() {
return subEntityValue;
}
public void setSubEntityValue(final String subEntityValue) {
this.subEntityValue = subEntityValue;
}
public String getOrderField() {
return orderField;
}
public void setOrderField(final String orderField) {
this.orderField = orderField;
}
public List<String> getRootBuilder() {
return rootBuilder;
}
public void setRootBuilder(final List<String> rootBuilder) {
this.rootBuilder = rootBuilder;
}
public Set<String> getSkipList() {
return skipList != null ? skipList : new HashSet<String>();
}
public void setSkipList(final Set<String> skipList) {
this.skipList = skipList;
}
public String getDedupRun() {
return dedupRun;
}
public void setDedupRun(final String dedupRun) {
this.dedupRun = dedupRun;
}
public double getThreshold() {
return threshold;
}
public void setThreshold(final double threshold) {
this.threshold = threshold;
}
public int getQueueMaxSize() {
return queueMaxSize;
}
public void setQueueMaxSize(final int queueMaxSize) {
this.queueMaxSize = queueMaxSize;
}
public int getGroupMaxSize() {
return groupMaxSize;
}
public void setGroupMaxSize(final int groupMaxSize) {
this.groupMaxSize = groupMaxSize;
}
public int getSlidingWindowSize() {
return slidingWindowSize;
}
public void setSlidingWindowSize(final int slidingWindowSize) {
this.slidingWindowSize = slidingWindowSize;
}
public String getConfigurationId() {
return configurationId;
}
public void setConfigurationId(final String configurationId) {
this.configurationId = configurationId;
}
public boolean isIncludeChildren() {
return includeChildren;
}
public void setIncludeChildren(final boolean includeChildren) {
this.includeChildren = includeChildren;
}
public int getMaxChildren() {
return maxChildren;
}
public void setMaxChildren(final int maxChildren) {
this.maxChildren = maxChildren;
}
public int getMaxIterations() {
return maxIterations;
}
public void setMaxIterations(int maxIterations) {
this.maxIterations = maxIterations;
}
public String getIdPath() {
return idPath;
}
public void setIdPath(String idPath) {
this.idPath = idPath;
}
/*
* (non-Javadoc)
* @see java.lang.Object#toString()
*/
@Override
public String toString() {
try {
return new ObjectMapper().writeValueAsString(this);
} catch (IOException e) {
throw new PaceException("unable to serialise " + this.getClass().getName(), e);
}
}
}

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package eu.dnetlib.pace.model;
import java.io.IOException;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.pace.clustering.ClusteringFunction;
import eu.dnetlib.pace.config.PaceConfig;
import eu.dnetlib.pace.util.PaceException;
public class ClusteringDef implements Serializable {
private String name;
private List<String> fields;
private Map<String, Integer> params;
public ClusteringDef() {
}
public String getName() {
return name;
}
public void setName(final String name) {
this.name = name;
}
public ClusteringFunction clusteringFunction() {
return PaceConfig.resolver.getClusteringFunction(getName(), params);
}
public List<String> getFields() {
return fields;
}
public void setFields(final List<String> fields) {
this.fields = fields;
}
public Map<String, Integer> getParams() {
return params;
}
public void setParams(final Map<String, Integer> params) {
this.params = params;
}
@Override
public String toString() {
try {
return new ObjectMapper().writeValueAsString(this);
} catch (IOException e) {
throw new PaceException("unable to serialise " + this.getClass().getName(), e);
}
}
}

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package eu.dnetlib.pace.model;
import java.io.Serializable;
import java.util.List;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.google.common.base.Splitter;
import com.google.common.collect.Lists;
import eu.dnetlib.pace.config.Type;
/**
* The schema is composed by field definitions (FieldDef). Each field has a type, a name, and an associated compare algorithm.
*/
public class FieldDef implements Serializable {
public final static String PATH_SEPARATOR = "/";
private String name;
private String path;
private Type type;
private boolean overrideMatch;
/**
* Sets maximum size for the repeatable fields in the model. -1 for unbounded size.
*/
private int size = -1;
/**
* Sets maximum length for field values in the model. -1 for unbounded length.
*/
private int length = -1;
public FieldDef() {
}
public String getName() {
return name;
}
public String getPath() {
return path;
}
public List<String> getPathList() {
return Lists.newArrayList(Splitter.on(PATH_SEPARATOR).split(getPath()));
}
public Type getType() {
return type;
}
public void setType(final Type type) {
this.type = type;
}
public boolean isOverrideMatch() {
return overrideMatch;
}
public void setOverrideMatch(final boolean overrideMatch) {
this.overrideMatch = overrideMatch;
}
public int getSize() {
return size;
}
public void setSize(int size) {
this.size = size;
}
public int getLength() {
return length;
}
public void setLength(int length) {
this.length = length;
}
public void setName(String name) {
this.name = name;
}
public void setPath(String path) {
this.path = path;
}
@Override
public String toString() {
try {
return new ObjectMapper().writeValueAsString(this);
} catch (JsonProcessingException e) {
return null;
}
}
}

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package eu.dnetlib.pace.model;
import java.nio.charset.Charset;
import java.text.Normalizer;
import java.util.List;
import java.util.Set;
import com.google.common.base.Joiner;
import com.google.common.base.Splitter;
import com.google.common.collect.Iterables;
import com.google.common.collect.Lists;
import com.google.common.hash.Hashing;
import eu.dnetlib.pace.common.AbstractPaceFunctions;
import eu.dnetlib.pace.util.Capitalise;
import eu.dnetlib.pace.util.DotAbbreviations;
public class Person {
private static final String UTF8 = "UTF-8";
private List<String> name = Lists.newArrayList();
private List<String> surname = Lists.newArrayList();
private List<String> fullname = Lists.newArrayList();
private final String original;
private static Set<String> particles = null;
public Person(String s, final boolean aggressive) {
original = s;
s = Normalizer.normalize(s, Normalizer.Form.NFD);
s = s.replaceAll("\\(.+\\)", "");
s = s.replaceAll("\\[.+\\]", "");
s = s.replaceAll("\\{.+\\}", "");
s = s.replaceAll("\\s+-\\s+", "-");
s = s.replaceAll("[\\p{Punct}&&[^,-]]", " ");
s = s.replaceAll("\\d", " ");
s = s.replaceAll("\\n", " ");
s = s.replaceAll("\\.", " ");
s = s.replaceAll("\\s+", " ");
if (aggressive) {
s = s.replaceAll("[\\p{InCombiningDiacriticalMarks}&&[^,-]]", "");
// s = s.replaceAll("[\\W&&[^,-]]", "");
}
if (s.contains(",")) { // if the name contains a comma it is easy derivable the name and the surname
final String[] arr = s.split(",");
if (arr.length == 1) {
fullname = splitTerms(arr[0]);
} else if (arr.length > 1) {
surname = splitTerms(arr[0]);
name = splitTerms(arr[1]);
fullname.addAll(surname);
fullname.addAll(name);
}
} else {
fullname = splitTerms(s);
int lastInitialPosition = fullname.size();
boolean hasSurnameInUpperCase = false;
for (int i = 0; i < fullname.size(); i++) {
final String term = fullname.get(i);
if (term.length() == 1) {
lastInitialPosition = i;
} else if (term.equals(term.toUpperCase())) {
hasSurnameInUpperCase = true;
}
}
if (lastInitialPosition < (fullname.size() - 1)) { // Case: Michele G. Artini
name = fullname.subList(0, lastInitialPosition + 1);
surname = fullname.subList(lastInitialPosition + 1, fullname.size());
} else if (hasSurnameInUpperCase) { // Case: Michele ARTINI
for (final String term : fullname) {
if ((term.length() > 1) && term.equals(term.toUpperCase())) {
surname.add(term);
} else {
name.add(term);
}
}
}
}
}
private List<String> splitTerms(final String s) {
if (particles == null) {
particles = AbstractPaceFunctions.loadFromClasspath("/eu/dnetlib/pace/config/name_particles.txt");
}
final List<String> list = Lists.newArrayList();
for (final String part : Splitter.on(" ").omitEmptyStrings().split(s)) {
if (!particles.contains(part.toLowerCase())) {
list.add(part);
}
}
return list;
}
public List<String> getName() {
return name;
}
public String getNameString() {
return Joiner.on(" ").join(getName());
}
public List<String> getSurname() {
return surname;
}
public List<String> getFullname() {
return fullname;
}
public String getOriginal() {
return original;
}
public String hash() {
return Hashing.murmur3_128().hashString(getNormalisedFullname(), Charset.forName(UTF8)).toString();
}
public String getNormalisedFirstName() {
return Joiner.on(" ").join(getCapitalFirstnames());
}
public String getNormalisedSurname() {
return Joiner.on(" ").join(getCapitalSurname());
}
public String getSurnameString() {
return Joiner.on(" ").join(getSurname());
}
public String getNormalisedFullname() {
return isAccurate() ? getNormalisedSurname() + ", " + getNormalisedFirstName() : Joiner.on(" ").join(fullname);
}
public List<String> getCapitalFirstnames() {
return Lists.newArrayList(Iterables.transform(getNameWithAbbreviations(), new Capitalise()));
}
public List<String> getCapitalSurname() {
return Lists.newArrayList(Iterables.transform(surname, new Capitalise()));
}
public List<String> getNameWithAbbreviations() {
return Lists.newArrayList(Iterables.transform(name, new DotAbbreviations()));
}
public boolean isAccurate() {
return ((name != null) && (surname != null) && !name.isEmpty() && !surname.isEmpty());
}
}

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package eu.dnetlib.pace.model;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.Set;
import com.google.common.collect.Lists;
import com.google.common.collect.Sets;
public class PersonComparatorUtils {
private static final int MAX_FULLNAME_LENGTH = 50;
public static Set<String> getNgramsForPerson(String fullname) {
Set<String> set = Sets.newHashSet();
if (fullname.length() > MAX_FULLNAME_LENGTH) {
return set;
}
Person p = new Person(fullname, true);
if (p.isAccurate()) {
for (String name : p.getName()) {
for (String surname : p.getSurname()) {
set.add((name.charAt(0) + "_" + surname).toLowerCase());
}
}
} else {
List<String> list = p.getFullname();
for (int i = 0; i < list.size(); i++) {
if (list.get(i).length() > 1) {
for (int j = 0; j < list.size(); j++) {
if (i != j) {
set.add((list.get(j).charAt(0) + "_" + list.get(i)).toLowerCase());
}
}
}
}
}
return set;
}
public static boolean areSimilar(String s1, String s2) {
Person p1 = new Person(s1, true);
Person p2 = new Person(s2, true);
if (p1.isAccurate() && p2.isAccurate()) {
return verifyNames(p1.getName(), p2.getName()) && verifySurnames(p1.getSurname(), p2.getSurname());
} else {
return verifyFullnames(p1.getFullname(), p2.getFullname());
}
}
private static boolean verifyNames(List<String> list1, List<String> list2) {
return verifySimilarity(extractExtendedNames(list1), extractExtendedNames(list2))
&& verifySimilarity(extractInitials(list1), extractInitials(list2));
}
private static boolean verifySurnames(List<String> list1, List<String> list2) {
if (list1.size() != list2.size()) {
return false;
}
for (int i = 0; i < list1.size(); i++) {
if (!list1.get(i).equalsIgnoreCase(list2.get(i))) {
return false;
}
}
return true;
}
private static boolean verifyFullnames(List<String> list1, List<String> list2) {
Collections.sort(list1);
Collections.sort(list2);
return verifySimilarity(extractExtendedNames(list1), extractExtendedNames(list2))
&& verifySimilarity(extractInitials(list1), extractInitials(list2));
}
private static List<String> extractExtendedNames(List<String> list) {
ArrayList<String> res = Lists.newArrayList();
for (String s : list) {
if (s.length() > 1) {
res.add(s.toLowerCase());
}
}
return res;
}
private static List<String> extractInitials(List<String> list) {
ArrayList<String> res = Lists.newArrayList();
for (String s : list) {
res.add(s.substring(0, 1).toLowerCase());
}
return res;
}
private static boolean verifySimilarity(List<String> list1, List<String> list2) {
if (list1.size() > list2.size()) {
return verifySimilarity(list2, list1);
}
// NB: List2 is greater than list1 (or equal)
int pos = -1;
for (String s : list1) {
int curr = list2.indexOf(s);
if (curr > pos) {
list2.set(curr, "*"); // I invalidate the found element, example: "amm - amm"
pos = curr;
} else {
return false;
}
}
return true;
}
}

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package eu.dnetlib.pace.model;
import java.util.Comparator;
import org.apache.spark.sql.Row;
import eu.dnetlib.pace.clustering.NGramUtils;
/**
* The Class MapDocumentComparator.
*/
public class RowDataOrderingComparator implements Comparator<Row> {
/** The comparator field. */
private final int comparatorField;
private final int identityFieldPosition;
/**
* Instantiates a new map document comparator.
*
* @param comparatorField
* the comparator field
*/
public RowDataOrderingComparator(final int comparatorField, int identityFieldPosition) {
this.comparatorField = comparatorField;
this.identityFieldPosition = identityFieldPosition;
}
/*
* (non-Javadoc)
* @see java.util.Comparator#compare(java.lang.Object, java.lang.Object)
*/
@Override
public int compare(final Row d1, final Row d2) {
if (d1 == null)
return d2 == null ? 0 : -1;
else if (d2 == null) {
return 1;
}
final String o1 = d1.getString(comparatorField);
final String o2 = d2.getString(comparatorField);
if (o1 == null)
return o2 == null ? 0 : -1;
else if (o2 == null) {
return 1;
}
final String to1 = NGramUtils.cleanupForOrdering(o1);
final String to2 = NGramUtils.cleanupForOrdering(o2);
int res = to1.compareTo(to2);
if (res == 0) {
res = o1.compareTo(o2);
if (res == 0) {
return d1.getString(identityFieldPosition).compareTo(d2.getString(identityFieldPosition));
}
}
return res;
}
}

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package eu.dnetlib.pace.model
import eu.dnetlib.pace.config.{DedupConfig, Type}
import eu.dnetlib.pace.util.{BlockProcessor, SparkReporter}
import org.apache.spark.SparkContext
import org.apache.spark.sql.catalyst.expressions.Literal
import org.apache.spark.sql.expressions._
import org.apache.spark.sql.functions.{col, lit, udf}
import org.apache.spark.sql.types._
import org.apache.spark.sql.{Column, Dataset, Row, functions}
import java.util.function.Predicate
import java.util.stream.Collectors
import scala.collection.JavaConversions._
import scala.collection.JavaConverters._
import scala.collection.mutable
case class SparkDeduper(conf: DedupConfig) extends Serializable {
val model: SparkModel = SparkModel(conf)
val dedup: (Dataset[Row] => Dataset[Row]) = df => {
df.transform(filterAndCleanup)
.transform(generateClustersWithCollect)
.transform(processBlocks)
}
val filterAndCleanup: (Dataset[Row] => Dataset[Row]) = df => {
val df_with_filters = conf.getPace.getModel.asScala.foldLeft(df)((res, fdef) => {
if (conf.blacklists.containsKey(fdef.getName)) {
res.withColumn(
fdef.getName + "_filtered",
filterColumnUDF(fdef).apply(new Column(fdef.getName))
)
} else {
res
}
})
df_with_filters
}
def filterColumnUDF(fdef: FieldDef): UserDefinedFunction = {
val blacklist: Predicate[String] = conf.blacklists().get(fdef.getName)
if (blacklist == null) {
throw new IllegalArgumentException("Column: " + fdef.getName + " does not have any filter")
} else {
fdef.getType match {
case Type.List | Type.JSON =>
udf[Array[String], Array[String]](values => {
values.filter((v: String) => !blacklist.test(v))
})
case _ =>
udf[String, String](v => {
if (blacklist.test(v)) ""
else v
})
}
}
}
val generateClustersWithCollect: (Dataset[Row] => Dataset[Row]) = df_with_filters => {
var df_with_clustering_keys: Dataset[Row] = null
for ((cd, idx) <- conf.clusterings().zipWithIndex) {
val inputColumns = cd.getFields().foldLeft(Seq[Column]())((acc, fName) => {
val column = if (conf.blacklists.containsKey(fName))
Seq(col(fName + "_filtered"))
else
Seq(col(fName))
acc ++ column
})
// Add 'key' column with the value generated by the given clustering definition
val ds: Dataset[Row] = df_with_filters
.withColumn("clustering", lit(cd.getName + "::" + idx))
.withColumn("key", functions.explode(clusterValuesUDF(cd).apply(functions.array(inputColumns: _*))))
// Add position column having the position of the row within the set of rows having the same key value ordered by the sorting value
.withColumn("position", functions.row_number().over(Window.partitionBy("key").orderBy(col(model.orderingFieldName), col(model.identifierFieldName))))
if (df_with_clustering_keys == null)
df_with_clustering_keys = ds
else
df_with_clustering_keys = df_with_clustering_keys.union(ds)
}
//TODO: analytics
val df_with_blocks = df_with_clustering_keys
// filter out rows with position exceeding the maxqueuesize parameter
.filter(col("position").leq(conf.getWf.getQueueMaxSize))
.groupBy("clustering", "key")
.agg(functions.collect_set(functions.struct(model.schema.fieldNames.map(col): _*)).as("block"))
.filter(functions.size(new Column("block")).gt(1))
df_with_blocks
}
def clusterValuesUDF(cd: ClusteringDef) = {
udf[mutable.WrappedArray[String], mutable.WrappedArray[Any]](values => {
values.flatMap(f => cd.clusteringFunction().apply(conf, Seq(f.toString).asJava).asScala)
})
}
val processBlocks: (Dataset[Row] => Dataset[Row]) = df => {
df.filter(functions.size(new Column("block")).geq(new Literal(2, DataTypes.IntegerType)))
.withColumn("relations", processBlock(df.sqlContext.sparkContext).apply(new Column("block")))
.select(functions.explode(new Column("relations")).as("relation"))
}
def processBlock(implicit sc: SparkContext) = {
val accumulators = SparkReporter.constructAccumulator(conf, sc)
udf[Array[(String, String)], mutable.WrappedArray[Row]](block => {
val reporter = new SparkReporter(accumulators)
val mapDocuments = block.asJava.stream()
.sorted(new RowDataOrderingComparator(model.orderingFieldPosition, model.identityFieldPosition))
.limit(conf.getWf.getQueueMaxSize)
.collect(Collectors.toList[Row]())
new BlockProcessor(conf, model.identityFieldPosition, model.orderingFieldPosition).processSortedRows(mapDocuments, reporter)
reporter.getRelations.asScala.toArray
}).asNondeterministic()
}
}

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package eu.dnetlib.pace.model
import com.jayway.jsonpath.{Configuration, JsonPath}
import eu.dnetlib.pace.config.{DedupConfig, Type}
import eu.dnetlib.pace.util.MapDocumentUtil
import org.apache.spark.sql.catalyst.encoders.RowEncoder
import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema
import org.apache.spark.sql.types.{DataTypes, Metadata, StructField, StructType}
import org.apache.spark.sql.{Dataset, Row}
import java.util.regex.Pattern
import scala.collection.JavaConverters._
case class SparkModel(conf: DedupConfig) {
private val URL_REGEX: Pattern = Pattern.compile("^\\s*(http|https|ftp)\\://.*")
private val CONCAT_REGEX: Pattern = Pattern.compile("\\|\\|\\|")
val identifierFieldName = "identifier"
val orderingFieldName = if (!conf.getWf.getOrderField.isEmpty) conf.getWf.getOrderField else identifierFieldName
val schema: StructType = {
// create an implicit identifier field
val identifier = new FieldDef()
identifier.setName(identifierFieldName)
identifier.setType(Type.String)
// Construct a Spark StructType representing the schema of the model
(Seq(identifier) ++ conf.getPace.getModel.asScala)
.foldLeft(
new StructType()
)((resType, fieldDef) => {
resType.add(fieldDef.getType match {
case Type.List | Type.JSON =>
StructField(fieldDef.getName, DataTypes.createArrayType(DataTypes.StringType), true, Metadata.empty)
case Type.DoubleArray =>
StructField(fieldDef.getName, DataTypes.createArrayType(DataTypes.DoubleType), true, Metadata.empty)
case _ =>
StructField(fieldDef.getName, DataTypes.StringType, true, Metadata.empty)
})
})
}
val identityFieldPosition: Int = schema.fieldIndex(identifierFieldName)
val orderingFieldPosition: Int = schema.fieldIndex(orderingFieldName)
val parseJsonDataset: (Dataset[String] => Dataset[Row]) = df => {
df.map(r => rowFromJson(r))(RowEncoder(schema))
}
def rowFromJson(json: String): Row = {
val documentContext =
JsonPath.using(Configuration.defaultConfiguration.addOptions(com.jayway.jsonpath.Option.SUPPRESS_EXCEPTIONS)).parse(json)
val values = new Array[Any](schema.size)
values(identityFieldPosition) = MapDocumentUtil.getJPathString(conf.getWf.getIdPath, documentContext)
schema.fieldNames.zipWithIndex.foldLeft(values) {
case ((res, (fname, index))) => {
val fdef = conf.getPace.getModelMap.get(fname)
if (fdef != null) {
res(index) = fdef.getType match {
case Type.String | Type.Int =>
MapDocumentUtil.truncateValue(
MapDocumentUtil.getJPathString(fdef.getPath, documentContext),
fdef.getLength
)
case Type.URL =>
var uv = MapDocumentUtil.getJPathString(fdef.getPath, documentContext)
if (!URL_REGEX.matcher(uv).matches)
uv = ""
uv
case Type.List | Type.JSON =>
MapDocumentUtil.truncateList(
MapDocumentUtil.getJPathList(fdef.getPath, documentContext, fdef.getType),
fdef.getSize
).toArray
case Type.StringConcat =>
val jpaths = CONCAT_REGEX.split(fdef.getPath)
MapDocumentUtil.truncateValue(
jpaths
.map(jpath => MapDocumentUtil.getJPathString(jpath, documentContext))
.mkString(" "),
fdef.getLength
)
case Type.DoubleArray =>
MapDocumentUtil.getJPathArray(fdef.getPath, json)
}
}
res
}
}
new GenericRowWithSchema(values, schema)
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("alwaysMatch")
public class AlwaysMatch<T> extends AbstractComparator<T> {
public AlwaysMatch(final Map<String, String> params) {
super(params, new com.wcohen.ss.JaroWinkler());
}
public AlwaysMatch(final double weight) {
super(weight, new com.wcohen.ss.JaroWinkler());
}
protected AlwaysMatch(final double weight, final AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
@Override
public double compare(final Object a, final Object b, final Config conf) {
return 1.0;
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(final double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.model.Person;
import eu.dnetlib.pace.tree.support.AbstractListComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("authorsMatch")
public class AuthorsMatch extends AbstractListComparator {
Map<String, String> params;
private double SURNAME_THRESHOLD;
private double NAME_THRESHOLD;
private double FULLNAME_THRESHOLD;
private String MODE; // full or surname
private int SIZE_THRESHOLD;
private String TYPE; // count or percentage
private int common;
public AuthorsMatch(Map<String, String> params) {
super(params, new com.wcohen.ss.JaroWinkler());
this.params = params;
MODE = params.getOrDefault("mode", "full");
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"));
SIZE_THRESHOLD = Integer.parseInt(params.getOrDefault("size_th", "20"));
TYPE = params.getOrDefault("type", "percentage");
common = 0;
}
protected AuthorsMatch(double w, AbstractStringDistance ssalgo) {
super(w, ssalgo);
}
@Override
public double compare(final List<String> a, final List<String> b, final Config conf) {
if (a.isEmpty() || b.isEmpty())
return -1;
if (a.size() > SIZE_THRESHOLD || b.size() > SIZE_THRESHOLD)
return 1.0;
List<Person> aList = a.stream().map(author -> new Person(author, false)).collect(Collectors.toList());
List<Person> bList = b.stream().map(author -> new Person(author, false)).collect(Collectors.toList());
common = 0;
// compare each element of List1 with each element of List2
for (Person p1 : aList)
for (Person p2 : bList) {
// both persons are inaccurate
if (!p1.isAccurate() && !p2.isAccurate()) {
// compare just normalized fullnames
String fullname1 = normalization(
p1.getNormalisedFullname().isEmpty() ? p1.getOriginal() : p1.getNormalisedFullname());
String fullname2 = normalization(
p2.getNormalisedFullname().isEmpty() ? p2.getOriginal() : p2.getNormalisedFullname());
if (ssalgo.score(fullname1, fullname2) > FULLNAME_THRESHOLD) {
common += 1;
break;
}
}
// one person is inaccurate
if (p1.isAccurate() ^ p2.isAccurate()) {
// prepare data
// data for the accurate person
String name = normalization(
p1.isAccurate() ? p1.getNormalisedFirstName() : p2.getNormalisedFirstName());
String surname = normalization(
p1.isAccurate() ? p1.getNormalisedSurname() : p2.getNormalisedSurname());
// data for the inaccurate person
String fullname = normalization(
p1.isAccurate()
? ((p2.getNormalisedFullname().isEmpty()) ? p2.getOriginal() : p2.getNormalisedFullname())
: (p1.getNormalisedFullname().isEmpty() ? p1.getOriginal() : 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);
if (TYPE.equals("percentage")) {
return (double) common / normFactor;
} else {
return (double) common;
}
}
public boolean compareSurname(Person p1, Person p2) {
return ssalgo
.score(
normalization(p1.getNormalisedSurname()), normalization(p2.getNormalisedSurname())) > SURNAME_THRESHOLD;
}
public boolean compareFirstname(Person p1, Person p2) {
if (p1.getNormalisedFirstName().length() <= 2 || p2.getNormalisedFirstName().length() <= 2) {
if (firstLC(p1.getNormalisedFirstName()).equals(firstLC(p2.getNormalisedFirstName())))
return true;
}
return ssalgo
.score(
normalization(p1.getNormalisedFirstName()),
normalization(p2.getNormalisedFirstName())) > NAME_THRESHOLD;
}
public String normalization(String s) {
return normalize(utf8(cleanup(s)));
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import java.util.Set;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("cityMatch")
public class CityMatch extends AbstractStringComparator {
private Map<String, String> params;
public CityMatch(Map<String, String> params) {
super(params);
this.params = params;
}
@Override
public double distance(final String a, final String b, final Config conf) {
String ca = cleanup(a);
String cb = cleanup(b);
ca = normalize(ca);
cb = normalize(cb);
ca = filterAllStopWords(ca);
cb = filterAllStopWords(cb);
Set<String> cities1 = getCities(ca, Integer.parseInt(params.getOrDefault("windowSize", "4")));
Set<String> cities2 = getCities(cb, Integer.parseInt(params.getOrDefault("windowSize", "4")));
Set<String> codes1 = citiesToCodes(cities1);
Set<String> codes2 = citiesToCodes(cities2);
// if no cities are detected, the comparator gives 1.0
if (codes1.isEmpty() && codes2.isEmpty())
return 1.0;
else {
if (codes1.isEmpty() ^ codes2.isEmpty())
return -1; // undefined if one of the two has no cities
return commonElementsPercentage(codes1, codes2);
}
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("cosineSimilarity")
public class CosineSimilarity extends AbstractComparator<double[]> {
Map<String, String> params;
public CosineSimilarity(Map<String, String> params) {
super(params);
}
@Override
public double compare(Object a, Object b, Config config) {
return compare((double[]) a, (double[]) b, config);
}
public double compare(final double[] a, final double[] b, final Config conf) {
if (a.length == 0 || b.length == 0)
return -1;
return cosineSimilarity(a, b);
}
double cosineSimilarity(double[] a, double[] b) {
double dotProduct = 0;
double normASum = 0;
double normBSum = 0;
for (int i = 0; i < a.length; i++) {
dotProduct += a[i] * b[i];
normASum += a[i] * a[i];
normBSum += b[i] * b[i];
}
double eucledianDist = Math.sqrt(normASum) * Math.sqrt(normBSum);
return dotProduct / eucledianDist;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* The Class ExactMatch.
*
* @author claudio
*/
@ComparatorClass("doiExactMatch")
public class DoiExactMatch extends ExactMatchIgnoreCase {
public final String PREFIX = "(http:\\/\\/dx\\.doi\\.org\\/)|(doi:)";
public DoiExactMatch(final Map<String, String> params) {
super(params);
}
@Override
protected String toString(final Object f) {
return super.toString(f).replaceAll(PREFIX, "");
}
}

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package eu.dnetlib.pace.tree;
import java.net.MalformedURLException;
import java.net.URL;
import java.util.Map;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("domainExactMatch")
public class DomainExactMatch extends ExactMatchIgnoreCase {
public DomainExactMatch(final Map<String, String> params) {
super(params);
}
@Override
protected String toString(final Object f) {
try {
return asUrl(super.toString(f)).getHost();
} catch (MalformedURLException e) {
return "";
}
}
private URL asUrl(final String value) throws MalformedURLException {
return new URL(value);
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("exactMatch")
public class ExactMatch extends AbstractStringComparator {
public ExactMatch(Map<String, String> params) {
super(params, new com.wcohen.ss.JaroWinkler());
}
public ExactMatch(final double weight) {
super(weight, new com.wcohen.ss.JaroWinkler());
}
protected ExactMatch(final double weight, final AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
@Override
public double distance(final String a, final String b, final Config conf) {
if (a.isEmpty() || b.isEmpty()) {
return -1.0; // return -1 if a field is missing
}
return a.equals(b) ? 1.0 : 0;
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(final double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("exactMatchIgnoreCase")
public class ExactMatchIgnoreCase extends AbstractStringComparator {
public ExactMatchIgnoreCase(Map<String, String> params) {
super(params);
}
@Override
public double compare(String a, String b, final Config conf) {
if (a.isEmpty() || b.isEmpty())
return -1;
return a.equalsIgnoreCase(b) ? 1 : 0;
}
protected String toString(final Object object) {
return toFirstString(object);
}
}

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package eu.dnetlib.pace.tree;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.stream.Collectors;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractListComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("instanceTypeMatch")
public class InstanceTypeMatch extends AbstractListComparator {
final Map<String, String> translationMap = new HashMap<>();
public InstanceTypeMatch(Map<String, String> params) {
super(params);
// jolly types
translationMap.put("Conference object", "*");
translationMap.put("Other literature type", "*");
translationMap.put("Unknown", "*");
// article types
translationMap.put("Article", "Article");
translationMap.put("Data Paper", "Article");
translationMap.put("Software Paper", "Article");
translationMap.put("Preprint", "Article");
// thesis types
translationMap.put("Thesis", "Thesis");
translationMap.put("Master thesis", "Thesis");
translationMap.put("Bachelor thesis", "Thesis");
translationMap.put("Doctoral thesis", "Thesis");
}
@Override
public double compare(final List<String> a, final List<String> b, final Config conf) {
if (a == null || b == null) {
return -1;
}
if (a.isEmpty() || b.isEmpty()) {
return -1;
}
final Set<String> ca = a.stream().map(this::translate).collect(Collectors.toSet());
final Set<String> cb = b.stream().map(this::translate).collect(Collectors.toSet());
// if at least one is a jolly type, it must produce a match
if (ca.contains("*") || cb.contains("*"))
return 1.0;
int incommon = Sets.intersection(ca, cb).size();
// if at least one is in common, it must produce a match
return incommon >= 1 ? 1 : 0;
}
public String translate(String term) {
return translationMap.getOrDefault(term, term);
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(final double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
//case class JaroWinkler(w: Double) extends SecondStringDistanceAlgo(w, new com.wcohen.ss.JaroWinkler())
@ComparatorClass("jaroWinkler")
public class JaroWinkler extends AbstractStringComparator {
public JaroWinkler(Map<String, String> params) {
super(params, new com.wcohen.ss.JaroWinkler());
}
public JaroWinkler(double weight) {
super(weight, new com.wcohen.ss.JaroWinkler());
}
protected JaroWinkler(double weight, AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
@Override
public double distance(String a, String b, final Config conf) {
String ca = cleanup(a);
String cb = cleanup(b);
return normalize(ssalgo.score(ca, cb));
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import java.util.Set;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("jaroWinklerNormalizedName")
public class JaroWinklerNormalizedName extends AbstractStringComparator {
private Map<String, String> params;
public JaroWinklerNormalizedName(Map<String, String> params) {
super(params, new com.wcohen.ss.JaroWinkler());
this.params = params;
}
public JaroWinklerNormalizedName(double weight) {
super(weight, new com.wcohen.ss.JaroWinkler());
}
protected JaroWinklerNormalizedName(double weight, AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
@Override
public double distance(String a, String b, final Config conf) {
String ca = cleanup(a);
String cb = cleanup(b);
ca = normalize(ca);
cb = normalize(cb);
ca = filterAllStopWords(ca);
cb = filterAllStopWords(cb);
Set<String> keywords1 = getKeywords(
ca, conf.translationMap(), Integer.parseInt(params.getOrDefault("windowSize", "4")));
Set<String> keywords2 = getKeywords(
cb, conf.translationMap(), Integer.parseInt(params.getOrDefault("windowSize", "4")));
Set<String> cities1 = getCities(ca, Integer.parseInt(params.getOrDefault("windowSize", "4")));
Set<String> cities2 = getCities(cb, Integer.parseInt(params.getOrDefault("windowSize", "4")));
ca = removeKeywords(ca, keywords1);
ca = removeKeywords(ca, cities1);
cb = removeKeywords(cb, keywords2);
cb = removeKeywords(cb, cities2);
ca = ca.replaceAll("[ ]{2,}", " ");
cb = cb.replaceAll("[ ]{2,}", " ");
if (ca.isEmpty() && cb.isEmpty())
return 1.0;
else
return normalize(ssalgo.score(ca, cb));
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
//case class JaroWinkler(w: Double) extends SecondStringDistanceAlgo(w, new com.wcohen.ss.JaroWinkler())
@ComparatorClass("jaroWinklerTitle")
public class JaroWinklerTitle extends AbstractStringComparator {
public JaroWinklerTitle(Map<String, String> params) {
super(params, new com.wcohen.ss.JaroWinkler());
}
public JaroWinklerTitle(double weight) {
super(weight, new com.wcohen.ss.JaroWinkler());
}
protected JaroWinklerTitle(double weight, AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
@Override
public double distance(String a, String b, final Config conf) {
String ca = cleanup(a);
String cb = cleanup(b);
boolean check = checkNumbers(ca, cb);
return check ? 0.5 : normalize(ssalgo.score(ca, cb));
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.stream.Collectors;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import com.google.common.collect.Sets;
import com.jayway.jsonpath.Configuration;
import com.jayway.jsonpath.DocumentContext;
import com.jayway.jsonpath.JsonPath;
import com.jayway.jsonpath.Option;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractListComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
import eu.dnetlib.pace.util.MapDocumentUtil;
@ComparatorClass("jsonListMatch")
public class JsonListMatch extends AbstractListComparator {
private static final Log log = LogFactory.getLog(JsonListMatch.class);
private Map<String, String> params;
private String MODE; // "percentage" or "count"
public JsonListMatch(final Map<String, String> params) {
super(params);
this.params = params;
MODE = params.getOrDefault("mode", "percentage");
}
@Override
public double compare(final List<String> sa, final List<String> sb, final Config conf) {
if (sa.isEmpty() || sb.isEmpty()) {
return -1;
}
final Set<String> ca = sa.stream().map(this::toComparableString).collect(Collectors.toSet());
final Set<String> cb = sb.stream().map(this::toComparableString).collect(Collectors.toSet());
int incommon = Sets.intersection(ca, cb).size();
int simDiff = Sets.symmetricDifference(ca, cb).size();
if (incommon + simDiff == 0) {
return 0.0;
}
if (MODE.equals("percentage"))
return (double) incommon / (incommon + simDiff);
else
return incommon;
}
// converts every json into a comparable string basing on parameters
private String toComparableString(String json) {
StringBuilder st = new StringBuilder(); // to build the string used for comparisons basing on the jpath into
// parameters
final DocumentContext documentContext = JsonPath
.using(Configuration.defaultConfiguration().addOptions(Option.SUPPRESS_EXCEPTIONS))
.parse(json);
// for each path in the param list
for (String key : params.keySet().stream().filter(k -> k.contains("jpath")).collect(Collectors.toList())) {
String path = params.get(key);
String value = MapDocumentUtil.getJPathString(path, documentContext);
if (value == null || value.isEmpty())
value = "";
st.append(value);
st.append("::");
}
st.setLength(st.length() - 2);
return st.toString();
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import java.util.Set;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("keywordMatch")
public class KeywordMatch extends AbstractStringComparator {
Map<String, String> params;
public KeywordMatch(Map<String, String> params) {
super(params);
this.params = params;
}
@Override
public double distance(final String a, final String b, final Config conf) {
String ca = cleanup(a);
String cb = cleanup(b);
ca = normalize(ca);
cb = normalize(cb);
ca = filterAllStopWords(ca);
cb = filterAllStopWords(cb);
Set<String> keywords1 = getKeywords(
ca, conf.translationMap(), Integer.parseInt(params.getOrDefault("windowSize", "4")));
Set<String> keywords2 = getKeywords(
cb, conf.translationMap(), Integer.parseInt(params.getOrDefault("windowSize", "4")));
Set<String> codes1 = toCodes(keywords1, conf.translationMap());
Set<String> codes2 = toCodes(keywords2, conf.translationMap());
// if no cities are detected, the comparator gives 1.0
if (codes1.isEmpty() && codes2.isEmpty())
return 1.0;
else {
if (codes1.isEmpty() ^ codes2.isEmpty())
return -1.0; // undefined if one of the two has no keywords
return commonElementsPercentage(codes1, codes2);
}
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("level2JaroWinkler")
public class Level2JaroWinkler extends AbstractStringComparator {
public Level2JaroWinkler(Map<String, String> params) {
super(params, new com.wcohen.ss.Level2JaroWinkler());
}
public Level2JaroWinkler(double w) {
super(w, new com.wcohen.ss.Level2JaroWinkler());
}
protected Level2JaroWinkler(double w, AbstractStringDistance ssalgo) {
super(w, ssalgo);
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("level2JaroWinklerTitle")
public class Level2JaroWinklerTitle extends AbstractStringComparator {
public Level2JaroWinklerTitle(Map<String, String> params) {
super(params, new com.wcohen.ss.Level2JaroWinkler());
}
public Level2JaroWinklerTitle(final double w) {
super(w, new com.wcohen.ss.Level2JaroWinkler());
}
protected Level2JaroWinklerTitle(final double w, final AbstractStringDistance ssalgo) {
super(w, ssalgo);
}
@Override
public double distance(final String a, final String b, final Config conf) {
final String ca = cleanup(a);
final String cb = cleanup(b);
final boolean check = checkNumbers(ca, cb);
if (check)
return 0.5;
return ssalgo.score(ca, cb);
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(final double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("level2Levenstein")
public class Level2Levenstein extends AbstractStringComparator {
public Level2Levenstein(Map<String, String> params) {
super(params, new com.wcohen.ss.Level2Levenstein());
}
public Level2Levenstein(double w) {
super(w, new com.wcohen.ss.Level2Levenstein());
}
protected Level2Levenstein(double w, AbstractStringDistance ssalgo) {
super(w, ssalgo);
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(double d) {
return 1 / Math.pow(Math.abs(d) + 1, 0.1);
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("levenstein")
public class Levenstein extends AbstractStringComparator {
public Levenstein(Map<String, String> params) {
super(params, new com.wcohen.ss.Levenstein());
}
public Levenstein(double w) {
super(w, new com.wcohen.ss.Levenstein());
}
protected Levenstein(double w, AbstractStringDistance ssalgo) {
super(w, ssalgo);
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(double d) {
return 1 / Math.pow(Math.abs(d) + 1, 0.1);
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("levensteinTitle")
public class LevensteinTitle extends AbstractStringComparator {
private static final Log log = LogFactory.getLog(LevensteinTitle.class);
public LevensteinTitle(Map<String, String> params) {
super(params, new com.wcohen.ss.Levenstein());
}
public LevensteinTitle(final double w) {
super(w, new com.wcohen.ss.Levenstein());
}
protected LevensteinTitle(final double w, final AbstractStringDistance ssalgo) {
super(w, ssalgo);
}
@Override
public double distance(final String a, final String b, final Config conf) {
final String ca = cleanup(a);
final String cb = cleanup(b);
final boolean check = checkNumbers(ca, cb);
if (check)
return 0.5;
return normalize(ssalgo.score(ca, cb), ca.length(), cb.length());
}
private double normalize(final double score, final int la, final int lb) {
return 1 - (Math.abs(score) / Math.max(la, lb));
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(final double d) {
return 1 / Math.pow(Math.abs(d) + 1, 0.1);
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* Compared compare between two titles, ignoring version numbers. Suitable for Software entities.
*/
@ComparatorClass("levensteinTitleIgnoreVersion")
public class LevensteinTitleIgnoreVersion extends AbstractStringComparator {
public LevensteinTitleIgnoreVersion(Map<String, String> params) {
super(params, new com.wcohen.ss.Levenstein());
}
public LevensteinTitleIgnoreVersion(final double w) {
super(w, new com.wcohen.ss.Levenstein());
}
protected LevensteinTitleIgnoreVersion(final double w, final AbstractStringDistance ssalgo) {
super(w, ssalgo);
}
@Override
public double distance(final String a, final String b, final Config conf) {
String ca = cleanup(a);
String cb = cleanup(b);
ca = ca.replaceAll("\\d", "").replaceAll(getRomans(ca), "").trim();
cb = cb.replaceAll("\\d", "").replaceAll(getRomans(cb), "").trim();
ca = filterAllStopWords(ca);
cb = filterAllStopWords(cb);
return normalize(ssalgo.score(ca, cb), ca.length(), cb.length());
}
private double normalize(final double score, final int la, final int lb) {
return 1 - (Math.abs(score) / Math.max(la, lb));
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(final double d) {
return 1 / Math.pow(Math.abs(d) + 1, 0.1);
}
}

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package eu.dnetlib.pace.tree;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractListComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* The Class Contains match
*
* @author miconis
* */
@ComparatorClass("listContainsMatch")
public class ListContainsMatch extends AbstractListComparator {
private Map<String, String> params;
private boolean CASE_SENSITIVE;
private String STRING;
private String AGGREGATOR;
public ListContainsMatch(Map<String, String> params) {
super(params);
this.params = params;
// read parameters
CASE_SENSITIVE = Boolean.parseBoolean(params.getOrDefault("caseSensitive", "false"));
STRING = params.get("string");
AGGREGATOR = params.get("bool");
}
@Override
public double compare(List<String> sa, List<String> sb, Config conf) {
if (sa.isEmpty() || sb.isEmpty()) {
return -1;
}
if (!CASE_SENSITIVE) {
sa = sa.stream().map(String::toLowerCase).collect(Collectors.toList());
sb = sb.stream().map(String::toLowerCase).collect(Collectors.toList());
STRING = STRING.toLowerCase();
}
switch (AGGREGATOR) {
case "AND":
if (sa.contains(STRING) && sb.contains(STRING))
return 1.0;
break;
case "OR":
if (sa.contains(STRING) || sb.contains(STRING))
return 1.0;
break;
case "XOR":
if (sa.contains(STRING) ^ sb.contains(STRING))
return 1.0;
break;
default:
return 0.0;
}
return 0.0;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("mustBeDifferent")
public class MustBeDifferent extends AbstractStringComparator {
public MustBeDifferent(Map<String, String> params) {
super(params, new com.wcohen.ss.Levenstein());
}
public MustBeDifferent(final double weight) {
super(weight, new com.wcohen.ss.JaroWinkler());
}
protected MustBeDifferent(final double weight, final AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
@Override
public double distance(final String a, final String b, final Config conf) {
return !a.equals(b) ? 1.0 : 0;
}
@Override
public double getWeight() {
return super.weight;
}
@Override
protected double normalize(final double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.Comparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* Not all fields of a document need to partecipate in the compare measure. We model those fields as having a
* NullDistanceAlgo.
*/
@ComparatorClass("null")
public class NullDistanceAlgo<T> implements Comparator<T> {
public NullDistanceAlgo(Map<String, String> params) {
}
@Override
public double compare(Object a, Object b, Config config) {
return 0;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("numbersComparator")
public class NumbersComparator extends AbstractStringComparator {
Map<String, String> params;
public NumbersComparator(Map<String, String> params) {
super(params);
this.params = params;
}
@Override
public double distance(String a, String b, Config conf) {
// extracts numbers from the field
String numbers1 = getNumbers(nfd(a));
String numbers2 = getNumbers(nfd(b));
if (numbers1.isEmpty() || numbers2.isEmpty())
return -1.0;
int n1 = Integer.parseInt(numbers1);
int n2 = Integer.parseInt(numbers2);
return Math.abs(n1 - n2);
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("numbersMatch")
public class NumbersMatch extends AbstractStringComparator {
public NumbersMatch(Map<String, String> params) {
super(params);
}
@Override
public double distance(String a, String b, Config conf) {
// extracts numbers from the field
String numbers1 = getNumbers(nfd(a));
String numbers2 = getNumbers(nfd(b));
if (numbers1.isEmpty() && numbers2.isEmpty())
return 1.0;
if (numbers1.isEmpty() || numbers2.isEmpty())
return -1.0;
if (numbers1.equals(numbers2))
return 1.0;
return 0.0;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("romansMatch")
public class RomansMatch extends AbstractStringComparator {
public RomansMatch(Map<String, String> params) {
super(params);
}
@Override
public double distance(String a, String b, Config conf) {
// extracts romans from the field
String romans1 = getRomans(nfd(a));
String romans2 = getRomans(nfd(b));
if (romans1.isEmpty() && romans2.isEmpty())
return 1.0;
if (romans1.isEmpty() || romans2.isEmpty())
return -1.0;
if (romans1.equals(romans2))
return 1.0;
return 0.0;
}
}

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package eu.dnetlib.pace.tree;
import java.util.List;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractListComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* Returns true if the number of values in the fields is the same.
*
* @author claudio
*/
@ComparatorClass("sizeMatch")
public class SizeMatch extends AbstractListComparator {
/**
* Instantiates a new size match.
*
* @param params
* the parameters
*/
public SizeMatch(final Map<String, String> params) {
super(params);
}
@Override
public double compare(final List<String> a, final List<String> b, final Config conf) {
if (a.isEmpty() || b.isEmpty())
return -1.0;
return a.size() == b.size() ? 1.0 : 0.0;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.tree.support.AbstractSortedComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* The Class SortedJaroWinkler.
*/
@ComparatorClass("sortedJaroWinkler")
public class SortedJaroWinkler extends AbstractSortedComparator {
public SortedJaroWinkler(Map<String, String> params) {
super(params, new com.wcohen.ss.Levenstein());
}
/**
* Instantiates a new sorted jaro winkler.
*
* @param weight
* the weight
*/
public SortedJaroWinkler(final double weight) {
super(weight, new com.wcohen.ss.JaroWinkler());
}
/**
* Instantiates a new sorted jaro winkler.
*
* @param weight
* the weight
* @param ssalgo
* the ssalgo
*/
protected SortedJaroWinkler(final double weight, final AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
/*
* (non-Javadoc)
* @see eu.dnetlib.pace.compare.DistanceAlgo#getWeight()
*/
@Override
public double getWeight() {
return super.weight;
}
/*
* (non-Javadoc)
* @see eu.dnetlib.pace.compare.SecondStringDistanceAlgo#normalize(double)
*/
@Override
protected double normalize(final double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.tree.support.AbstractSortedComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* The Class SortedJaroWinkler.
*/
@ComparatorClass("sortedLevel2JaroWinkler")
public class SortedLevel2JaroWinkler extends AbstractSortedComparator {
/**
* Instantiates a new sorted jaro winkler.
*
* @param weight
* the weight
*/
public SortedLevel2JaroWinkler(final double weight) {
super(weight, new com.wcohen.ss.Level2JaroWinkler());
}
public SortedLevel2JaroWinkler(final Map<String, String> params) {
super(params, new com.wcohen.ss.Level2JaroWinkler());
}
/**
* Instantiates a new sorted jaro winkler.
*
* @param weight
* the weight
* @param ssalgo
* the ssalgo
*/
protected SortedLevel2JaroWinkler(final double weight, final AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
/*
* (non-Javadoc)
* @see eu.dnetlib.pace.compare.DistanceAlgo#getWeight()
*/
@Override
public double getWeight() {
return super.weight;
}
/*
* (non-Javadoc)
* @see eu.dnetlib.pace.compare.SecondStringDistanceAlgo#normalize(double)
*/
@Override
protected double normalize(final double d) {
return d;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* The Class Contains match
*
* @author miconis
* */
@ComparatorClass("stringContainsMatch")
public class StringContainsMatch extends AbstractStringComparator {
private Map<String, String> params;
private boolean CASE_SENSITIVE;
private String STRING;
private String AGGREGATOR;
public StringContainsMatch(Map<String, String> params) {
super(params);
this.params = params;
// read parameters
CASE_SENSITIVE = Boolean.parseBoolean(params.getOrDefault("caseSensitive", "false"));
STRING = params.get("string");
AGGREGATOR = params.get("aggregator");
}
@Override
public double distance(final String a, final String b, final Config conf) {
String ca = a;
String cb = b;
if (!CASE_SENSITIVE) {
ca = a.toLowerCase();
cb = b.toLowerCase();
STRING = STRING.toLowerCase();
}
if (AGGREGATOR != null) {
switch (AGGREGATOR) {
case "AND":
if (ca.contains(STRING) && cb.contains(STRING))
return 1.0;
break;
case "OR":
if (ca.contains(STRING) || cb.contains(STRING))
return 1.0;
break;
case "XOR":
if (ca.contains(STRING) ^ cb.contains(STRING))
return 1.0;
break;
default:
return 0.0;
}
}
return 0.0;
}
}

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package eu.dnetlib.pace.tree;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import com.google.common.collect.Sets;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractListComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("stringListMatch")
public class StringListMatch extends AbstractListComparator {
private static final Log log = LogFactory.getLog(StringListMatch.class);
private Map<String, String> params;
final private String TYPE; // percentage or count
public StringListMatch(final Map<String, String> params) {
super(params);
this.params = params;
TYPE = params.getOrDefault("type", "percentage");
}
@Override
public double compare(final List<String> a, final List<String> b, final Config conf) {
final Set<String> pa = new HashSet<>(a);
final Set<String> pb = new HashSet<>(b);
if (pa.isEmpty() || pb.isEmpty()) {
return -1; // return undefined if one of the two lists is empty
}
int incommon = Sets.intersection(pa, pb).size();
int simDiff = Sets.symmetricDifference(pa, pb).size();
if (incommon + simDiff == 0) {
return 0.0;
}
if (TYPE.equals("percentage"))
return (double) incommon / (incommon + simDiff);
else
return incommon;
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import org.apache.commons.lang3.StringUtils;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* The Class SubStringLevenstein.
*/
@ComparatorClass("subStringLevenstein")
public class SubStringLevenstein extends AbstractStringComparator {
/**
* The limit.
*/
protected int limit;
/**
* Instantiates a new sub string levenstein.
*
* @param w the w
*/
public SubStringLevenstein(final double w) {
super(w, new com.wcohen.ss.Levenstein());
}
public SubStringLevenstein(Map<String, String> params) {
super(params, new com.wcohen.ss.Levenstein());
this.limit = Integer.parseInt(params.getOrDefault("limit", "1"));
}
/**
* Instantiates a new sub string levenstein.
*
* @param w the w
* @param limit the limit
*/
public SubStringLevenstein(final double w, final int limit) {
super(w, new com.wcohen.ss.Levenstein());
this.limit = limit;
}
/**
* Instantiates a new sub string levenstein.
*
* @param w the w
* @param limit the limit
* @param ssalgo the ssalgo
*/
protected SubStringLevenstein(final double w, final int limit, final AbstractStringDistance ssalgo) {
super(w, ssalgo);
this.limit = limit;
}
/*
* (non-Javadoc)
* @see eu.dnetlib.pace.compare.SecondStringDistanceAlgo#compare(eu.dnetlib.pace.model.Field,
* eu.dnetlib.pace.model.Field)
*/
@Override
public double distance(final String a, final String b, final Config conf) {
return distance(StringUtils.left(a, limit), StringUtils.left(b, limit), conf);
}
/*
* (non-Javadoc)
* @see eu.dnetlib.pace.compare.DistanceAlgo#getWeight()
*/
@Override
public double getWeight() {
return super.weight;
}
/*
* (non-Javadoc)
* @see eu.dnetlib.pace.compare.SecondStringDistanceAlgo#normalize(double)
*/
@Override
protected double normalize(final double d) {
return 1 / Math.pow(Math.abs(d) + 1, 0.1);
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* Returns true if the titles in the given documents contains the same numbers, false otherwise.
*
* @author claudio
*
*/
@ComparatorClass("titleVersionMatch")
public class TitleVersionMatch extends AbstractStringComparator {
public TitleVersionMatch(final Map<String, String> params) {
super(params);
}
@Override
public double compare(final String valueA, final String valueB, final Config conf) {
if (valueA.isEmpty() || valueB.isEmpty())
return -1;
return notNull(valueA) && notNull(valueB) && !checkNumbers(valueA, valueB) ? 1 : 0;
}
@Override
public String toString() {
return getClass().getSimpleName() + ":" + super.toString();
}
protected String toString(final Object object) {
return toFirstString(object);
}
}

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package eu.dnetlib.pace.tree;
import java.net.MalformedURLException;
import java.net.URL;
import java.util.Map;
import org.apache.commons.lang3.StringUtils;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.ComparatorClass;
@ComparatorClass("urlMatcher")
public class UrlMatcher extends Levenstein {
private Map<String, String> params;
public UrlMatcher(Map<String, String> params) {
super(params);
this.params = params;
}
public UrlMatcher(double weight, Map<String, String> params) {
super(weight);
this.params = params;
}
public void setParams(Map<String, String> params) {
this.params = params;
}
@Override
public double distance(String a, String b, final Config conf) {
final URL urlA = asUrl(a);
final URL urlB = asUrl(b);
if (!urlA.getHost().equalsIgnoreCase(urlB.getHost())) {
return 0.0;
}
Double hostW = Double.parseDouble(params.getOrDefault("host", "0.5"));
Double pathW = Double.parseDouble(params.getOrDefault("path", "0.5"));
if (StringUtils.isBlank(urlA.getPath()) || StringUtils.isBlank(urlB.getPath())) {
return hostW * 0.5;
}
return hostW + pathW * super.distance(urlA.getPath(), urlB.getPath(), conf);
}
private URL asUrl(final String value) {
try {
return new URL(value);
} catch (MalformedURLException e) {
// should not happen as checked by pace typing
throw new IllegalStateException("invalid URL: " + value);
}
}
protected String toString(final Object object) {
return toFirstString(object);
}
}

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package eu.dnetlib.pace.tree;
import java.util.Map;
import org.apache.commons.lang3.StringUtils;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.tree.support.AbstractStringComparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
/**
* Returns true if the year of the date field in the given documents are the same, false when any of the two is invalid or it's missing.
*
* @author claudio
*/
@ComparatorClass("yearMatch")
public class YearMatch extends AbstractStringComparator {
private int limit = 4;
public YearMatch(final Map<String, String> params) {
super(params);
}
@Override
public double compare(final String a, final String b, final Config conf) {
final String valueA = getNumbers(getFirstValue(a));
final String valueB = getNumbers(getFirstValue(b));
if (valueA.isEmpty() || valueB.isEmpty())
return -1;
final boolean lengthMatch = checkLength(valueA) && checkLength(valueB);
final boolean onemissing = valueA.isEmpty() || valueB.isEmpty();
return lengthMatch && valueA.equals(valueB) || onemissing ? 1 : 0;
}
protected boolean checkLength(final String s) {
return s.length() == limit;
}
protected String getFirstValue(final String value) {
return (value != null) && !value.isEmpty() ? StringUtils.left(value, limit) : "";
}
@Override
public String toString() {
return getClass().getSimpleName() + ":" + super.toString();
}
}

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package eu.dnetlib.pace.tree.support;
import java.util.List;
import java.util.Map;
import com.google.common.base.Joiner;
import com.google.common.collect.Lists;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.common.AbstractPaceFunctions;
import eu.dnetlib.pace.config.Config;
public abstract class AbstractComparator<T> extends AbstractPaceFunctions implements Comparator<T> {
/** The ssalgo. */
protected AbstractStringDistance ssalgo;
/** The weight. */
protected double weight = 0.0;
private Map<String, String> params;
protected AbstractComparator(Map<String, String> params) {
this.params = params;
}
protected AbstractComparator(Map<String, String> params, final AbstractStringDistance ssalgo) {
this.params = params;
this.weight = 1.0;
this.ssalgo = ssalgo;
}
/**
* Instantiates a new second string compare algo.
*
* @param weight
* the weight
* @param ssalgo
* the ssalgo
*/
protected AbstractComparator(final double weight, final AbstractStringDistance ssalgo) {
this.ssalgo = ssalgo;
this.weight = weight;
}
protected AbstractComparator(final AbstractStringDistance ssalgo) {
this.ssalgo = ssalgo;
}
/**
* Normalize.
*
* @param d
* the d
* @return the double
*/
protected double normalize(double d) {
return d;
}
/**
* Distance.
*
* @param a
* the a
* @param b
* the b
* @return the double
*/
protected double distance(final String a, final String b, final Config conf) {
if (a.isEmpty() || b.isEmpty()) {
return -1; // return -1 if a field is missing
}
double score = ssalgo.score(a, b);
return normalize(score);
}
protected double compare(final String a, final String b, final Config conf) {
if (a.isEmpty() || b.isEmpty())
return -1;
return distance(a, b, conf);
}
/**
* Convert the given argument to a List of Strings
*
* @param object
* function argument
* @return the list
*/
protected List<String> toList(final Object object) {
if (object instanceof List) {
return (List<String>) object;
}
return Lists.newArrayList(object.toString());
}
/**
* Convert the given argument to a String
*
* @param object
* function argument
* @return the list
*/
protected String toString(final Object object) {
if (object instanceof List) {
List<String> l = (List<String>) object;
return Joiner.on(" ").join(l);
}
return object.toString();
}
protected String toFirstString(final Object object) {
if (object instanceof List) {
List<String> l = (List<String>) object;
return l.isEmpty() ? "" : l.get(0);
}
return object.toString();
}
public double getWeight() {
return this.weight;
}
}

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package eu.dnetlib.pace.tree.support;
import java.util.List;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
abstract public class AbstractListComparator extends AbstractComparator<List<String>> {
protected AbstractListComparator(Map<String, String> params) {
super(params);
}
protected AbstractListComparator(Map<String, String> params, AbstractStringDistance ssalgo) {
super(params, ssalgo);
}
protected AbstractListComparator(double weight, AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
protected AbstractListComparator(AbstractStringDistance ssalgo) {
super(ssalgo);
}
@Override
public double compare(Object a, Object b, Config conf) {
return compare(toList(a), toList(b), conf);
}
public double compare(final List<String> a, final List<String> b, final Config conf) {
if (a.isEmpty() || b.isEmpty())
return -1;
return distance(concat(a), concat(b), conf);
}
}

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package eu.dnetlib.pace.tree.support;
import java.util.Collections;
import java.util.List;
import java.util.Map;
import com.google.common.collect.Lists;
import com.wcohen.ss.AbstractStringDistance;
public abstract class AbstractSortedComparator extends AbstractListComparator {
/**
* Instantiates a new sorted second string compare algo.
*
* @param weight
* the weight
* @param ssalgo
* the ssalgo
*/
protected AbstractSortedComparator(final double weight, final AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
protected AbstractSortedComparator(final Map<String, String> params, final AbstractStringDistance ssalgo) {
super(Double.parseDouble(params.get("weight")), ssalgo);
}
@Override
protected List<String> toList(final Object object) {
if (object instanceof List) {
List<String> fl = (List<String>) object;
List<String> values = Lists.newArrayList(fl);
Collections.sort(values);
return values;
}
return Lists.newArrayList(object.toString());
}
}

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package eu.dnetlib.pace.tree.support;
import java.util.Map;
import com.wcohen.ss.AbstractStringDistance;
import eu.dnetlib.pace.config.Config;
public abstract class AbstractStringComparator extends AbstractComparator<String> {
protected AbstractStringComparator(Map<String, String> params) {
super(params);
}
protected AbstractStringComparator(Map<String, String> params, AbstractStringDistance ssalgo) {
super(params, ssalgo);
}
protected AbstractStringComparator(double weight, AbstractStringDistance ssalgo) {
super(weight, ssalgo);
}
protected AbstractStringComparator(AbstractStringDistance ssalgo) {
super(ssalgo);
}
public double distance(final String a, final String b, final Config conf) {
if (a.isEmpty() || b.isEmpty()) {
return -1; // return -1 if a field is missing
}
double score = ssalgo.score(a, b);
return normalize(score);
}
@Override
public double compare(Object a, Object b, Config conf) {
return compare(toString(a), toString(b), conf);
}
public double compare(final String a, final String b, final Config conf) {
if (a.isEmpty() || b.isEmpty())
return -1;
return distance(a, b, conf);
}
}

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package eu.dnetlib.pace.tree.support;
import eu.dnetlib.pace.util.PaceException;
public enum AggType {
W_MEAN, // weighted mean
AVG, // average
SUM, MAX, MIN, AND, // used for necessary conditions
OR; // used for sufficient conditions
public static AggType getEnum(String value) {
try {
return AggType.valueOf(value);
} catch (IllegalArgumentException e) {
throw new PaceException("Undefined aggregation type", e);
}
}
}

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package eu.dnetlib.pace.tree.support;
import eu.dnetlib.pace.config.Config;
public interface Comparator<T> {
/*
* return : -1 -> can't decide (i.e. missing field) >0 -> similarity degree (depends on the algorithm)
*/
public double compare(Object a, Object b, Config conf);
}

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package eu.dnetlib.pace.tree.support;
import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
@Retention(RetentionPolicy.RUNTIME)
@Target(ElementType.TYPE)
public @interface ComparatorClass {
public String value();
}

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package eu.dnetlib.pace.tree.support;
import java.io.IOException;
import java.io.Serializable;
import java.util.Map;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.pace.util.PaceException;
/**
* The class that defines the configuration of each field in the decision tree.
* */
public class FieldConf implements Serializable {
private String field; // name of the field on which apply the comparator
private String comparator; // comparator name
private double weight = 1.0; // weight for the field (to be used in the aggregation)
private Map<String, String> params; // parameters
private boolean countIfUndefined;
public boolean isCountIfUndefined() {
return countIfUndefined;
}
public void setCountIfUndefined(boolean countIfUndefined) {
this.countIfUndefined = countIfUndefined;
}
public FieldConf() {
}
public FieldConf(String field, String comparator, double weight, Map<String, String> params,
boolean countIfUndefined) {
this.field = field;
this.comparator = comparator;
this.weight = weight;
this.params = params;
this.countIfUndefined = countIfUndefined;
}
public String getField() {
return field;
}
public void setField(String field) {
this.field = field;
}
public String getComparator() {
return comparator;
}
public void setComparator(String comparator) {
this.comparator = comparator;
}
public double getWeight() {
return weight;
}
public void setWeight(double weight) {
this.weight = weight;
}
public Map<String, String> getParams() {
return params;
}
public void setParams(Map<String, String> params) {
this.params = params;
}
@Override
public String toString() {
try {
return new ObjectMapper().writeValueAsString(this);
} catch (IOException e) {
throw new PaceException("Impossible to convert to JSON: ", e);
}
}
}

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package eu.dnetlib.pace.tree.support;
import java.io.IOException;
import java.io.Serializable;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.pace.util.PaceException;
/**
* The class that contains the result of each comparison in the decision tree
* */
public class FieldStats implements Serializable {
private double weight; // weight for the field (to be used in the aggregation)
private double threshold; // threshold for the field (to be used in some kind of aggregations)
private double result; // the result of the comparison
private Object a;
private Object b;
private boolean countIfUndefined;
public FieldStats(double weight, double threshold, double result, boolean countIfUndefined, Object a, Object b) {
this.weight = weight;
this.threshold = threshold;
this.result = result;
this.countIfUndefined = countIfUndefined;
this.a = a;
this.b = b;
}
public double getThreshold() {
return threshold;
}
public void setThreshold(double threshold) {
this.threshold = threshold;
}
public double getWeight() {
return weight;
}
public void setWeight(double weight) {
this.weight = weight;
}
public double getResult() {
return result;
}
public void setResult(double result) {
this.result = result;
}
public boolean isCountIfUndefined() {
return countIfUndefined;
}
public void setCountIfUndefined(boolean countIfUndefined) {
this.countIfUndefined = countIfUndefined;
}
public Object getA() {
return a;
}
public void setA(Object a) {
this.a = a;
}
public Object getB() {
return b;
}
public void setB(Object b) {
this.b = b;
}
@Override
public String toString() {
try {
return new ObjectMapper().writeValueAsString(this);
} catch (IOException e) {
throw new PaceException("Impossible to convert to JSON: ", e);
}
}
}

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package eu.dnetlib.pace.tree.support;
public enum MatchType {
MATCH, NO_MATCH, UNDEFINED;
public static MatchType parse(String value) {
if (MATCH.name().equals(value)) {
return MATCH;
} else if (NO_MATCH.name().equals(value)) {
return NO_MATCH;
} else {
return UNDEFINED;
}
// try {
// return MatchType.valueOf(value);
// }
// catch (IllegalArgumentException e) {
// return MatchType.UNDEFINED; //return UNDEFINED if the enum is not parsable
// }
}
}

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package eu.dnetlib.pace.tree.support;
import java.io.IOException;
import java.io.Serializable;
import java.util.List;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.types.ArrayType;
import org.apache.spark.sql.types.DataType;
import org.apache.spark.sql.types.StringType;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.config.PaceConfig;
import eu.dnetlib.pace.util.PaceException;
public class TreeNodeDef implements Serializable {
final static String CROSS_COMPARE = "crossCompare";
private List<FieldConf> fields;
private AggType aggregation;
private double threshold;
private String positive;
private String negative;
private String undefined;
boolean ignoreUndefined;
public TreeNodeDef(List<FieldConf> fields, AggType aggregation, double threshold, String positive, String negative,
String undefined, boolean ignoreUndefined) {
this.fields = fields;
this.aggregation = aggregation;
this.threshold = threshold;
this.positive = positive;
this.negative = negative;
this.undefined = undefined;
this.ignoreUndefined = ignoreUndefined;
}
public TreeNodeDef() {
}
// function for the evaluation of the node
public TreeNodeStats evaluate(Row doc1, Row doc2, Config conf) {
TreeNodeStats stats = new TreeNodeStats();
// for each field in the node, it computes the
for (FieldConf fieldConf : fields) {
double weight = fieldConf.getWeight();
double result;
Object value1 = getJavaValue(doc1, fieldConf.getField());
Object value2 = getJavaValue(doc2, fieldConf.getField());
// if the param specifies a cross comparison (i.e. compare elements from different fields), compute the
// result for both sides and return the maximum
String crossField = fieldConf.getParams().get(CROSS_COMPARE);
if (crossField != null) {
double result1 = comparator(fieldConf).compare(value1, getJavaValue(doc2, crossField), conf);
double result2 = comparator(fieldConf).compare(getJavaValue(doc1, crossField), value2, conf);
result = Math.max(result1, result2);
} else {
result = comparator(fieldConf).compare(value1, value2, conf);
}
stats
.addFieldStats(
fieldConf.getComparator() + " on " + fieldConf.getField() + " " + fields.indexOf(fieldConf),
new FieldStats(
weight,
Double.parseDouble(fieldConf.getParams().getOrDefault("threshold", "1.0")),
result,
fieldConf.isCountIfUndefined(),
value1,
value2));
}
return stats;
}
public Object getJavaValue(Row row, String name) {
int pos = row.fieldIndex(name);
if (pos >= 0) {
DataType dt = row.schema().fields()[pos].dataType();
if (dt instanceof StringType) {
return row.getString(pos);
} else if (dt instanceof ArrayType) {
return row.getList(pos);
}
}
return null;
}
private Comparator comparator(final FieldConf field) {
return PaceConfig.resolver.getComparator(field.getComparator(), field.getParams());
}
public List<FieldConf> getFields() {
return fields;
}
public void setFields(List<FieldConf> fields) {
this.fields = fields;
}
public AggType getAggregation() {
return aggregation;
}
public void setAggregation(AggType aggregation) {
this.aggregation = aggregation;
}
public double getThreshold() {
return threshold;
}
public void setThreshold(double threshold) {
this.threshold = threshold;
}
public String getPositive() {
return positive;
}
public void setPositive(String positive) {
this.positive = positive;
}
public String getNegative() {
return negative;
}
public void setNegative(String negative) {
this.negative = negative;
}
public String getUndefined() {
return undefined;
}
public void setUndefined(String undefined) {
this.undefined = undefined;
}
public boolean isIgnoreUndefined() {
return ignoreUndefined;
}
public void setIgnoreUndefined(boolean ignoreUndefined) {
this.ignoreUndefined = ignoreUndefined;
}
@Override
public String toString() {
try {
return new ObjectMapper().writeValueAsString(this);
} catch (IOException e) {
throw new PaceException("Impossible to convert to JSON: ", e);
}
}
}

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package eu.dnetlib.pace.tree.support;
import java.io.Serializable;
import java.util.HashMap;
import java.util.Map;
public class TreeNodeStats implements Serializable {
private Map<String, FieldStats> results; // this is an accumulator for the results of the node
public TreeNodeStats() {
this.results = new HashMap<>();
}
public Map<String, FieldStats> getResults() {
return results;
}
public void addFieldStats(String id, FieldStats fieldStats) {
this.results.put(id, fieldStats);
}
public int fieldsCount() {
return this.results.size();
}
public int undefinedCount() {
int undefinedCount = 0;
for (FieldStats fs : this.results.values()) {
if (fs.getResult() == -1)
undefinedCount++;
}
return undefinedCount;
}
public double scoreSum() {
double scoreSum = 0.0;
for (FieldStats fs : this.results.values()) {
if (fs.getResult() >= 0.0) {
scoreSum += fs.getResult();
}
}
return scoreSum;
}
// return the sum of the weights without considering the fields with countIfMissing=false && result=-1
public double weightSum() {
double weightSum = 0.0;
for (FieldStats fs : this.results.values()) {
if (fs.getResult() >= 0.0 || (fs.getResult() < 0.0 && fs.isCountIfUndefined())) {
weightSum += fs.getWeight();
}
}
return weightSum;
}
public double weightedScoreSum() {
double weightedScoreSum = 0.0;
for (FieldStats fs : this.results.values()) {
if (fs.getResult() >= 0.0) {
weightedScoreSum += fs.getResult() * fs.getWeight();
}
}
return weightedScoreSum;
}
public double max() {
double max = -1.0;
for (FieldStats fs : this.results.values()) {
if (fs.getResult() > max)
max = fs.getResult();
}
return max;
}
public double min() {
double min = 100.0; // random high value
for (FieldStats fs : this.results.values()) {
if (fs.getResult() < min) {
if (fs.getResult() >= 0.0 || (fs.getResult() == -1 && fs.isCountIfUndefined()))
min = fs.getResult();
}
}
return min;
}
// if at least one is true, return 1.0
public double or() {
for (FieldStats fieldStats : this.results.values()) {
if (fieldStats.getResult() >= fieldStats.getThreshold())
return 1.0;
}
return 0.0;
}
// if at least one is false, return 0.0
public double and() {
for (FieldStats fieldStats : this.results.values()) {
if (fieldStats.getResult() == -1) {
if (fieldStats.isCountIfUndefined())
return 0.0;
} else {
if (fieldStats.getResult() < fieldStats.getThreshold())
return 0.0;
}
}
return 1.0;
}
public double getFinalScore(AggType aggregation) {
switch (aggregation) {
case AVG:
return scoreSum() / fieldsCount();
case SUM:
return scoreSum();
case MAX:
return max();
case MIN:
return min();
case W_MEAN:
return weightedScoreSum() / weightSum();
case OR:
return or();
case AND:
return and();
default:
return 0.0;
}
}
}

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package eu.dnetlib.pace.tree.support;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.spark.sql.Row;
import eu.dnetlib.pace.config.Config;
import eu.dnetlib.pace.util.PaceException;
/**
* The compare between two documents is given by the weighted mean of the field distances
*/
public class TreeProcessor {
private static final Log log = LogFactory.getLog(TreeProcessor.class);
private Config config;
public TreeProcessor(final Config config) {
this.config = config;
}
// row based copies
public boolean compare(final Row a, final Row b) {
// evaluate the decision tree
return evaluateTree(a, b).getResult() == MatchType.MATCH;
}
public TreeStats evaluateTree(final Row doc1, final Row doc2) {
TreeStats treeStats = new TreeStats();
String nextNodeName = "start";
do {
TreeNodeDef currentNode = config.decisionTree().get(nextNodeName);
// throw an exception if the node doesn't exist
if (currentNode == null)
throw new PaceException("Missing tree node: " + nextNodeName);
TreeNodeStats stats = currentNode.evaluate(doc1, doc2, config);
treeStats.addNodeStats(nextNodeName, stats);
// if ignoreUndefined=false the miss is considered as undefined
if (!currentNode.isIgnoreUndefined() && stats.undefinedCount() > 0) {
nextNodeName = currentNode.getUndefined();
}
// if ignoreUndefined=true the miss is ignored and the score computed anyway
else if (stats.getFinalScore(currentNode.getAggregation()) >= currentNode.getThreshold()) {
nextNodeName = currentNode.getPositive();
} else {
nextNodeName = currentNode.getNegative();
}
} while (MatchType.parse(nextNodeName) == MatchType.UNDEFINED);
treeStats.setResult(MatchType.parse(nextNodeName));
return treeStats;
}
public double computeScore(final Row doc1, final Row doc2) {
String nextNodeName = "start";
double score = 0.0;
do {
TreeNodeDef currentNode = config.decisionTree().get(nextNodeName);
// throw an exception if the node doesn't exist
if (currentNode == null)
throw new PaceException("The Tree Node doesn't exist: " + nextNodeName);
TreeNodeStats stats = currentNode.evaluate(doc1, doc2, config);
score = stats.getFinalScore(currentNode.getAggregation());
// if ignoreUndefined=false the miss is considered as undefined
if (!currentNode.isIgnoreUndefined() && stats.undefinedCount() > 0) {
nextNodeName = currentNode.getUndefined();
}
// if ignoreUndefined=true the miss is ignored and the score computed anyway
else if (stats.getFinalScore(currentNode.getAggregation()) >= currentNode.getThreshold()) {
nextNodeName = currentNode.getPositive();
} else {
nextNodeName = currentNode.getNegative();
}
} while (MatchType.parse(nextNodeName) == MatchType.UNDEFINED);
return score;
}
}

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package eu.dnetlib.pace.tree.support;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.pace.util.PaceException;
public class TreeStats {
// <layer_id, <field:comparator, result>>
Map<String, TreeNodeStats> stats;
MatchType result;
public TreeStats() {
this.stats = new HashMap<>();
this.result = MatchType.NO_MATCH;
}
public MatchType getResult() {
return this.result;
}
public void setResult(MatchType result) {
this.result = result;
}
public Map<String, TreeNodeStats> getStats() {
return stats;
}
public void setStats(Map<String, TreeNodeStats> stats) {
this.stats = stats;
}
public void addNodeStats(String layerID, TreeNodeStats treeNodeStats) {
this.stats.put(layerID, treeNodeStats);
}
@Override
public String toString() {
try {
return new ObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
} catch (IOException e) {
throw new PaceException("Impossible to convert to JSON: ", e);
}
}
}

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package eu.dnetlib.pace.util;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.lang3.StringUtils;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.types.ArrayType;
import org.apache.spark.sql.types.DataType;
import org.apache.spark.sql.types.StringType;
import eu.dnetlib.pace.config.DedupConfig;
import eu.dnetlib.pace.config.WfConfig;
import eu.dnetlib.pace.tree.support.TreeProcessor;
public class BlockProcessor {
public static final List<String> accumulators = new ArrayList<>();
private static final Log log = LogFactory.getLog(BlockProcessor.class);
private DedupConfig dedupConf;
private final int identifierFieldPos;
private final int orderFieldPos;
public static void constructAccumulator(final DedupConfig dedupConf) {
accumulators.add(String.format("%s::%s", dedupConf.getWf().getEntityType(), "records per hash key = 1"));
accumulators
.add(
String
.format(
"%s::%s", dedupConf.getWf().getEntityType(), "missing " + dedupConf.getWf().getOrderField()));
accumulators
.add(
String
.format(
"%s::%s", dedupConf.getWf().getEntityType(),
String
.format(
"Skipped records for count(%s) >= %s", dedupConf.getWf().getOrderField(),
dedupConf.getWf().getGroupMaxSize())));
accumulators.add(String.format("%s::%s", dedupConf.getWf().getEntityType(), "skip list"));
accumulators.add(String.format("%s::%s", dedupConf.getWf().getEntityType(), "dedupSimilarity (x2)"));
accumulators
.add(String.format("%s::%s", dedupConf.getWf().getEntityType(), "d < " + dedupConf.getWf().getThreshold()));
}
public BlockProcessor(DedupConfig dedupConf, int identifierFieldPos, int orderFieldPos) {
this.dedupConf = dedupConf;
this.identifierFieldPos = identifierFieldPos;
this.orderFieldPos = orderFieldPos;
}
public void processSortedRows(final List<Row> documents, final Reporter context) {
if (documents.size() > 1) {
// log.info("reducing key: '" + key + "' records: " + q.size());
processRows(documents, context);
} else {
context.incrementCounter(dedupConf.getWf().getEntityType(), "records per hash key = 1", 1);
}
}
private void processRows(final List<Row> queue, final Reporter context) {
for (int pivotPos = 0; pivotPos < queue.size(); pivotPos++) {
final Row pivot = queue.get(pivotPos);
final String idPivot = pivot.getString(identifierFieldPos); // identifier
final Object fieldsPivot = getJavaValue(pivot, orderFieldPos);
final String fieldPivot = (fieldsPivot == null) ? "" : fieldsPivot.toString();
final WfConfig wf = dedupConf.getWf();
if (fieldPivot != null) {
int i = 0;
for (int windowPos = pivotPos + 1; windowPos < queue.size(); windowPos++) {
final Row curr = queue.get(windowPos);
final String idCurr = curr.getString(identifierFieldPos); // identifier
if (mustSkip(idCurr)) {
context.incrementCounter(wf.getEntityType(), "skip list", 1);
break;
}
if (++i > wf.getSlidingWindowSize()) {
break;
}
final Object fieldsCurr = getJavaValue(curr, orderFieldPos);
final String fieldCurr = (fieldsCurr == null) ? null : fieldsCurr.toString();
if (!idCurr.equals(idPivot) && (fieldCurr != null)) {
final TreeProcessor treeProcessor = new TreeProcessor(dedupConf);
emitOutput(treeProcessor.compare(pivot, curr), idPivot, idCurr, context);
}
}
}
}
}
public Object getJavaValue(Row row, int pos) {
DataType dt = row.schema().fields()[pos].dataType();
if (dt instanceof StringType) {
return row.getString(pos);
} else if (dt instanceof ArrayType) {
return row.getList(pos);
}
return null;
}
private void emitOutput(final boolean result, final String idPivot, final String idCurr, final Reporter context) {
if (result) {
if (idPivot.compareTo(idCurr) <= 0) {
writeSimilarity(context, idPivot, idCurr);
} else {
writeSimilarity(context, idCurr, idPivot);
}
context.incrementCounter(dedupConf.getWf().getEntityType(), "dedupSimilarity (x2)", 1);
} else {
context.incrementCounter(dedupConf.getWf().getEntityType(), "d < " + dedupConf.getWf().getThreshold(), 1);
}
}
private boolean mustSkip(final String idPivot) {
return dedupConf.getWf().getSkipList().contains(getNsPrefix(idPivot));
}
private String getNsPrefix(final String id) {
return StringUtils.substringBetween(id, "|", "::");
}
private void writeSimilarity(final Reporter context, final String from, final String to) {
final String type = dedupConf.getWf().getEntityType();
context.emit(type, from, to);
}
}

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package eu.dnetlib.pace.util;
import org.apache.commons.lang3.text.WordUtils;
import com.google.common.base.Function;
public class Capitalise implements Function<String, String> {
private final char[] DELIM = {
' ', '-'
};
@Override
public String apply(final String s) {
return WordUtils.capitalize(s.toLowerCase(), DELIM);
}
};

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package eu.dnetlib.pace.util;
import com.google.common.base.Function;
public class DotAbbreviations implements Function<String, String> {
@Override
public String apply(String s) {
return s.length() == 1 ? s + "." : s;
}
};

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package eu.dnetlib.pace.util;
import java.math.BigDecimal;
import java.util.ArrayList;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.concurrent.ConcurrentHashMap;
import java.util.function.Predicate;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.jayway.jsonpath.DocumentContext;
import com.jayway.jsonpath.JsonPath;
import com.jayway.jsonpath.spi.cache.Cache;
import com.jayway.jsonpath.spi.cache.CacheProvider;
import eu.dnetlib.pace.config.Type;
import net.minidev.json.JSONArray;
public class MapDocumentUtil {
public static final String URL_REGEX = "^(http|https|ftp)\\://.*";
public static Predicate<String> urlFilter = s -> s.trim().matches(URL_REGEX);
static {
CacheProvider.setCache(new Cache() {
private final ConcurrentHashMap<String, JsonPath> jsonPathCache = new ConcurrentHashMap();
@Override
public JsonPath get(String key) {
return jsonPathCache.get(key);
}
@Override
public void put(String key, JsonPath value) {
jsonPathCache.put(key, value);
}
});
}
public static String getJPathString(final String jsonPath, final String json) {
try {
Object o = JsonPath.read(json, jsonPath);
if (o instanceof String)
return (String) o;
if (o instanceof JSONArray && ((JSONArray) o).size() > 0)
return (String) ((JSONArray) o).get(0);
return "";
} catch (Exception e) {
return "";
}
}
public static double[] getJPathArray(final String jsonPath, final String json) {
try {
Object o = JsonPath.read(json, jsonPath);
if (o instanceof double[])
return (double[]) o;
if (o instanceof JSONArray) {
Object[] objects = ((JSONArray) o).toArray();
double[] array = new double[objects.length];
for (int i = 0; i < objects.length; i++) {
if (objects[i] instanceof BigDecimal)
array[i] = ((BigDecimal) objects[i]).doubleValue();
else
array[i] = (double) objects[i];
}
return array;
}
return new double[0];
} catch (Exception e) {
e.printStackTrace();
return new double[0];
}
}
public static String truncateValue(String value, int length) {
if (value == null)
return "";
if (length == -1 || length > value.length())
return value;
return value.substring(0, length);
}
public static List<String> truncateList(List<String> list, int size) {
if (size == -1 || size > list.size())
return list;
return list.subList(0, size);
}
public static String getJPathString(final String jsonPath, final DocumentContext json) {
try {
Object o = json.read(jsonPath);
if (o instanceof String)
return (String) o;
if (o instanceof JSONArray && ((JSONArray) o).size() > 0)
return (String) ((JSONArray) o).get(0);
return "";
} catch (Exception e) {
return "";
}
}
public static List<String> getJPathList(String path, DocumentContext json, Type type) {
// if (type == Type.List)
// return JsonPath.using(Configuration.defaultConfiguration().addOptions(Option.ALWAYS_RETURN_LIST,
// Option.SUPPRESS_EXCEPTIONS)).parse(json).read(path);
Object jresult;
List<String> result = new ArrayList<>();
try {
jresult = json.read(path);
} catch (Throwable e) {
return result;
}
if (jresult instanceof JSONArray) {
((JSONArray) jresult).forEach(it -> {
try {
result.add(new ObjectMapper().writeValueAsString(it));
} catch (JsonProcessingException e) {
}
});
return result;
}
if (jresult instanceof LinkedHashMap) {
try {
result.add(new ObjectMapper().writeValueAsString(jresult));
} catch (JsonProcessingException e) {
}
return result;
}
if (jresult instanceof String) {
result.add((String) jresult);
}
return result;
}
}

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package eu.dnetlib.pace.util;
public class PaceException extends RuntimeException {
public PaceException(String s, Throwable e) {
super(s, e);
}
public PaceException(String s) {
super(s);
}
}

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package eu.dnetlib.pace.util;
import java.io.Serializable;
import java.lang.reflect.InvocationTargetException;
import java.util.Map;
import java.util.stream.Collectors;
import org.reflections.Reflections;
import eu.dnetlib.pace.clustering.ClusteringClass;
import eu.dnetlib.pace.clustering.ClusteringFunction;
import eu.dnetlib.pace.tree.support.Comparator;
import eu.dnetlib.pace.tree.support.ComparatorClass;
public class PaceResolver implements Serializable {
public static final Reflections CLUSTERING_RESOLVER = new Reflections("eu.dnetlib.pace.clustering");
public static final Reflections COMPARATOR_RESOLVER = new Reflections("eu.dnetlib.pace.tree");
private final Map<String, Class<ClusteringFunction>> clusteringFunctions;
private final Map<String, Class<Comparator>> comparators;
public PaceResolver() {
this.clusteringFunctions = CLUSTERING_RESOLVER
.getTypesAnnotatedWith(ClusteringClass.class)
.stream()
.filter(ClusteringFunction.class::isAssignableFrom)
.collect(
Collectors
.toMap(
cl -> cl.getAnnotation(ClusteringClass.class).value(), cl -> (Class<ClusteringFunction>) cl));
this.comparators = COMPARATOR_RESOLVER
.getTypesAnnotatedWith(ComparatorClass.class)
.stream()
.filter(Comparator.class::isAssignableFrom)
.collect(
Collectors.toMap(cl -> cl.getAnnotation(ComparatorClass.class).value(), cl -> (Class<Comparator>) cl));
}
public ClusteringFunction getClusteringFunction(String name, Map<String, Integer> params) throws PaceException {
try {
return clusteringFunctions.get(name).getDeclaredConstructor(Map.class).newInstance(params);
} catch (InstantiationException | IllegalAccessException | InvocationTargetException
| NoSuchMethodException e) {
throw new PaceException(name + " not found ", e);
}
}
public Comparator getComparator(String name, Map<String, String> params) throws PaceException {
try {
return comparators.get(name).getDeclaredConstructor(Map.class).newInstance(params);
} catch (InstantiationException | IllegalAccessException | InvocationTargetException | NoSuchMethodException
| NullPointerException e) {
throw new PaceException(name + " not found ", e);
}
}
}

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package eu.dnetlib.pace.util;
import java.io.Serializable;
public interface Reporter extends Serializable {
void incrementCounter(String counterGroup, String counterName, long delta);
void emit(String type, String from, String to);
}

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package eu.dnetlib.pace.util;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import org.apache.spark.SparkContext;
import org.apache.spark.util.LongAccumulator;
import eu.dnetlib.pace.config.DedupConfig;
import scala.Serializable;
import scala.Tuple2;
public class SparkReporter implements Serializable, Reporter {
private final List<Tuple2<String, String>> relations = new ArrayList<>();
private final Map<String, LongAccumulator> accumulators;
public SparkReporter(Map<String, LongAccumulator> accumulators) {
this.accumulators = accumulators;
}
public void incrementCounter(
String counterGroup,
String counterName,
long delta,
Map<String, LongAccumulator> accumulators) {
final String accumulatorName = String.format("%s::%s", counterGroup, counterName);
if (accumulators.containsKey(accumulatorName)) {
accumulators.get(accumulatorName).add(delta);
}
}
@Override
public void incrementCounter(String counterGroup, String counterName, long delta) {
incrementCounter(counterGroup, counterName, delta, accumulators);
}
@Override
public void emit(String type, String from, String to) {
relations.add(new Tuple2<>(from, to));
}
public List<Tuple2<String, String>> getRelations() {
return relations;
}
public static Map<String, LongAccumulator> constructAccumulator(
final DedupConfig dedupConf, final SparkContext context) {
Map<String, LongAccumulator> accumulators = new HashMap<>();
String acc1 = String.format("%s::%s", dedupConf.getWf().getEntityType(), "records per hash key = 1");
accumulators.put(acc1, context.longAccumulator(acc1));
String acc2 = String
.format(
"%s::%s",
dedupConf.getWf().getEntityType(), "missing " + dedupConf.getWf().getOrderField());
accumulators.put(acc2, context.longAccumulator(acc2));
String acc3 = String
.format(
"%s::%s",
dedupConf.getWf().getEntityType(),
String
.format(
"Skipped records for count(%s) >= %s",
dedupConf.getWf().getOrderField(), dedupConf.getWf().getGroupMaxSize()));
accumulators.put(acc3, context.longAccumulator(acc3));
String acc4 = String.format("%s::%s", dedupConf.getWf().getEntityType(), "skip list");
accumulators.put(acc4, context.longAccumulator(acc4));
String acc5 = String.format("%s::%s", dedupConf.getWf().getEntityType(), "dedupSimilarity (x2)");
accumulators.put(acc5, context.longAccumulator(acc5));
String acc6 = String
.format(
"%s::%s", dedupConf.getWf().getEntityType(), "d < " + dedupConf.getWf().getThreshold());
accumulators.put(acc6, context.longAccumulator(acc6));
return accumulators;
}
}

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{
"wf" : {
"threshold" : "$threshold$",
"dedupRun" : "$run$",
"entityType" : "$entityType$",
"subEntityType" : "$subEntityType$",
"subEntityValue" : "$subEntityValue$",
"orderField" : "$orderField$",
"queueMaxSize" : "$queueMaxSize$",
"groupMaxSize" : "$groupMaxSize$",
"slidingWindowSize" : "$slidingWindowSize$",
"rootBuilder" : [ $rootBuilder:{"$it$"};separator=", "$ ],
"includeChildren" : "$includeChildren$",
"configurationId" : "$configurationId$"
},
"pace" : {
"clustering" : [
],
"sufficientConditions" : [
],
"necessaryConditions" : [
],
"model" : [
],
"blacklists" : { }
}
}

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