jarowinklernormalizedname splitted in 3 different comparators: citymatch, keywordmatch and jarowinkler. Implementation of the TreeStatistic support functions
This commit is contained in:
parent
c687956371
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ddd40540aa
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@ -13,7 +13,6 @@ public class RandomClusteringFunction extends AbstractClusteringFunction {
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@Override
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protected Collection<String> doApply(final Config conf, String s) {
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// TODO Auto-generated method stub
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return null;
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}
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@ -216,12 +216,17 @@ public abstract class AbstractPaceFunctions {
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Set<String> k1 = keywordsToCodes(s1, translationMap);
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Set<String> k2 = keywordsToCodes(s2, translationMap);
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int longer = (k1.size()>k2.size())?k1.size():k2.size();
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if (k1.isEmpty() || k2.isEmpty())
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return 1.0;
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else
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return (double)CollectionUtils.intersection(k1,k2).size()/(double)longer;
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return commonElementsPercentage(k1, k2);
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}
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public double commonElementsPercentage(Set<String> s1, Set<String> s2){
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int longer = (s1.size()>s2.size())?s1.size():s2.size();
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return (double)CollectionUtils.intersection(s1,s2).size()/(double)longer;
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}
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//convert the set of keywords to codes
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@ -0,0 +1,47 @@
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package eu.dnetlib.pace.tree;
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import eu.dnetlib.pace.config.Config;
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import eu.dnetlib.pace.tree.support.AbstractComparator;
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import eu.dnetlib.pace.tree.support.ComparatorClass;
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import java.util.Map;
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import java.util.Set;
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@ComparatorClass("cityMatch")
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public class CityMatch extends AbstractComparator {
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private Map<String, Number> params;
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public CityMatch(Map<String, Number> params) {
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super(params);
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this.params = params;
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}
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@Override
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public double distance(final String a, final String b, final Config conf) {
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String ca = cleanup(a);
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String cb = cleanup(b);
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ca = normalize(ca);
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cb = normalize(cb);
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ca = filterAllStopWords(ca);
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cb = filterAllStopWords(cb);
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Set<String> cities1 = getCities(ca, params.getOrDefault("windowSize", 4).intValue());
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Set<String> cities2 = getCities(cb, params.getOrDefault("windowSize", 4).intValue());
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Set<String> codes1 = citiesToCodes(cities1);
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Set<String> codes2 = citiesToCodes(cities2);
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//if no cities are detected, the comparator gives 1.0
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if (codes1.isEmpty() && codes2.isEmpty())
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return 1.0;
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else {
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if (codes1.isEmpty() ^ codes2.isEmpty())
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return -1; //undefined if one of the two has no cities
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return commonElementsPercentage(codes1, codes2) > params.getOrDefault("threshold", 0).intValue() ? 1.0 : 0.0;
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}
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}
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}
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@ -45,10 +45,6 @@ public class JaroWinklerNormalizedName extends AbstractComparator {
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Set<String> cities1 = getCities(ca, params.getOrDefault("windowSize", 4).intValue());
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Set<String> cities2 = getCities(cb, params.getOrDefault("windowSize", 4).intValue());
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if (checkCities(cities1,cities2)) {
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if (keywordsCompare(keywords1, keywords2, conf.translationMap())>params.getOrDefault("threshold", 0.5).doubleValue()) {
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ca = removeKeywords(ca, keywords1);
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ca = removeKeywords(ca, cities1);
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cb = removeKeywords(cb, keywords2);
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@ -58,27 +54,6 @@ public class JaroWinklerNormalizedName extends AbstractComparator {
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return 1.0;
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else
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return normalize(ssalgo.score(ca,cb));
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}
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}
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return 0.0;
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}
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//returns true if at least 1 city is in common
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//returns true if no cities are contained in names
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//returns false if one of the two names have no city
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public boolean checkCities(Set<String> s1, Set<String> s2){
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Set<String> c1 = citiesToCodes(s1);
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Set<String> c2 = citiesToCodes(s2);
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if (c1.isEmpty() && c2.isEmpty())
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return true;
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else {
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if (c1.isEmpty() ^ c2.isEmpty())
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return false;
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return CollectionUtils.intersection(c1, c2).size() > 0;
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}
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}
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@Override
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@ -0,0 +1,47 @@
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package eu.dnetlib.pace.tree;
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import eu.dnetlib.pace.config.Config;
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import eu.dnetlib.pace.tree.support.AbstractComparator;
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import eu.dnetlib.pace.tree.support.ComparatorClass;
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import java.util.Map;
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import java.util.Set;
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@ComparatorClass("keywordMatch")
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public class KeywordMatch extends AbstractComparator {
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Map<String, Number> params;
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public KeywordMatch(Map<String, Number> params) {
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super(params);
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this.params = params;
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}
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@Override
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public double distance(final String a, final String b, final Config conf) {
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String ca = cleanup(a);
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String cb = cleanup(b);
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ca = normalize(ca);
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cb = normalize(cb);
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ca = filterAllStopWords(ca);
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cb = filterAllStopWords(cb);
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Set<String> keywords1 = getKeywords(ca, conf.translationMap(), params.getOrDefault("windowSize", 4).intValue());
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Set<String> keywords2 = getKeywords(cb, conf.translationMap(), params.getOrDefault("windowSize", 4).intValue());
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Set<String> codes1 = toCodes(keywords1, conf.translationMap());
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Set<String> codes2 = toCodes(keywords2, conf.translationMap());
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//if no cities are detected, the comparator gives 1.0
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if (codes1.isEmpty() && codes2.isEmpty())
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return 1.0;
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else {
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if (codes1.isEmpty() ^ codes2.isEmpty())
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return -1; //undefined if one of the two has no keywords
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return commonElementsPercentage(codes1, codes2) > params.getOrDefault("threshold", 0).intValue() ? 1.0 : 0.0;
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}
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}
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}
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@ -0,0 +1,54 @@
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package eu.dnetlib.pace.tree.support;
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import eu.dnetlib.pace.util.PaceException;
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import org.codehaus.jackson.map.ObjectMapper;
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import java.io.IOException;
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import java.io.Serializable;
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public class FieldStats implements Serializable {
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private double weight; //weight for the field (to be used in the aggregation)
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private double result; //the result of the comparison
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private boolean countIfUndefined;
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public FieldStats(double weight, double result, boolean countIfUndefined) {
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this.weight = weight;
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this.result = result;
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this.countIfUndefined = countIfUndefined;
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}
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public double getWeight() {
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return weight;
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}
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public void setWeight(double weight) {
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this.weight = weight;
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}
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public double getResult() {
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return result;
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}
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public void setResult(double result) {
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this.result = result;
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}
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public boolean isCountIfUndefined() {
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return countIfUndefined;
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}
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public void setCountIfUndefined(boolean countIfUndefined) {
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this.countIfUndefined = countIfUndefined;
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}
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@Override
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public String toString(){
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try {
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return new ObjectMapper().writeValueAsString(this);
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} catch (IOException e) {
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throw new PaceException("Impossible to convert to JSON: ", e);
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}
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}
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}
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@ -39,7 +39,6 @@ public class TreeNodeDef implements Serializable {
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public TreeNodeStats evaluate(MapDocument doc1, MapDocument doc2, Config conf) {
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TreeNodeStats stats = new TreeNodeStats();
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stats.setFieldsCount(fields.size());
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for (FieldConf fieldConf : fields) {
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@ -47,16 +46,7 @@ public class TreeNodeDef implements Serializable {
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double result = comparator(fieldConf).compare(doc1.getFieldMap().get(fieldConf.getField()), doc2.getFieldMap().get(fieldConf.getField()), conf);
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if (result == -1) { //if the comparison is undefined
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stats.incrementUndefinedCount();
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if (fieldConf.isCountIfUndefined()) { //if it must be taken into account, increment weights (i.e. the average would be lower)
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stats.incrementWeightsSum(weight);
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}
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}
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else { //if the field is not missing
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stats.incrementScoresSum(weight * result);
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stats.incrementWeightsSum(weight);
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}
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stats.addFieldStats(fieldConf.getComparator() + " on " + fieldConf.getField(), new FieldStats(weight, result, fieldConf.isCountIfUndefined()));
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}
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@ -1,90 +1,108 @@
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package eu.dnetlib.pace.tree.support;
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import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics;
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import java.io.Serializable;
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import java.util.HashMap;
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import java.util.Map;
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public class TreeNodeStats implements Serializable {
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private DescriptiveStatistics stats;
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private int undefinedCount = 0; //counter for the number of undefined comparisons between the fields in the tree node
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private int fieldsCount = 0;
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private double weightsSum = 0.0;
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private Map<String, FieldStats> results; //this is an accumulator for the results of the node
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public TreeNodeStats(){
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this.stats = new DescriptiveStatistics();
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this.results = new HashMap<>();
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}
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public TreeNodeStats(int undefinedCount, int fieldsCount, double weightsSum) {
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this.undefinedCount = undefinedCount;
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this.fieldsCount = fieldsCount;
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this.weightsSum = weightsSum;
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public Map<String, FieldStats> getResults() {
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return results;
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}
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public DescriptiveStatistics getStats() {
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return stats;
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public void addFieldStats(String id, FieldStats fieldStats){
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this.results.put(id, fieldStats);
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}
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public void setStats(DescriptiveStatistics stats) {
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this.stats = stats;
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public int fieldsCount(){
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return this.results.size();
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}
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public int getUndefinedCount() {
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public int undefinedCount(){
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int undefinedCount = 0;
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for(FieldStats fs: this.results.values()){
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if(fs.getResult() == -1)
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undefinedCount ++;
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}
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return undefinedCount;
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}
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public void setUndefinedCount(int undefinedCount) {
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this.undefinedCount = undefinedCount;
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public double scoreSum(){
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double scoreSum = 0.0;
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for(FieldStats fs: this.results.values()){
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if(fs.getResult()>=0.0) {
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scoreSum += fs.getResult();
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}
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}
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return scoreSum;
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}
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public int getFieldsCount() {
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return fieldsCount;
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//return the sum of the weights without considering the fields with countIfMissing=false && result=-1
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public double weightSum(){
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double weightSum = 0.0;
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for(FieldStats fs: this.results.values()){
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if(fs.getResult()>=0.0 || (fs.getResult()<0.0 && fs.isCountIfUndefined())) {
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weightSum += fs.getWeight();
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}
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}
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return weightSum;
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}
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public void setFieldsCount(int fields) {
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this.fieldsCount = fields;
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public double weightedScoreSum(){
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double weightedScoreSum = 0.0;
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for(FieldStats fs: this.results.values()){
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if(fs.getResult()>=0.0) {
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weightedScoreSum += fs.getResult()*fs.getWeight();
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}
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}
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return weightedScoreSum;
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}
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public double getWeightsSum() {
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return weightsSum;
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public double max(){
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double max = -1.0;
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for(FieldStats fs: this.results.values()){
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if(fs.getResult()>max)
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max = fs.getResult();
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}
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return max;
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}
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public void setWeightsSum(double weightsSum) {
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this.weightsSum = weightsSum;
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public double min(){
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double min = 100.0; //random high value
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for(FieldStats fs: this.results.values()){
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if(fs.getResult()<min) {
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if (fs.getResult()>=0.0 || (fs.getResult() == -1 && fs.isCountIfUndefined()))
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min = fs.getResult();
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}
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public void incrementWeightsSum(double delta){
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this.weightsSum += delta;
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}
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public void incrementUndefinedCount(){
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this.undefinedCount += 1;
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}
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public void incrementScoresSum(double delta){
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this.stats.addValue(delta);
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return min;
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}
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public double getFinalScore(AggType aggregation){
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switch (aggregation){
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case AVG:
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return stats.getMean();
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return scoreSum()/fieldsCount();
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case SUM:
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return stats.getSum();
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return scoreSum();
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case SC:
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case OR:
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case MAX:
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return stats.getMax();
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return max();
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case NC:
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case AND:
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case MIN:
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return stats.getMin();
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return min();
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case W_MEAN:
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return stats.getSum()/weightsSum;
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return weightedScoreSum()/weightSum();
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default:
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return 0.0;
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}
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}
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}
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@ -6,6 +6,7 @@ import eu.dnetlib.pace.util.PaceException;
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import org.apache.commons.logging.Log;
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import org.apache.commons.logging.LogFactory;
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import java.io.Serializable;
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import java.util.Map;
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/**
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@ -24,10 +25,12 @@ public class TreeProcessor {
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public boolean compare(final MapDocument a, final MapDocument b) {
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//evaluate the decision tree
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return evaluateTree(a, b) == MatchType.MATCH;
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return evaluateTree(a, b).getResult() == MatchType.MATCH;
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}
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public MatchType evaluateTree(final MapDocument doc1, final MapDocument doc2){
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public TreeStats evaluateTree(final MapDocument doc1, final MapDocument doc2){
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TreeStats treeStats = new TreeStats();
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String current = "start";
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@ -39,9 +42,10 @@ public class TreeProcessor {
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throw new PaceException("The Tree Node doesn't exist: " + current);
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TreeNodeStats stats = currentNode.evaluate(doc1, doc2, config);
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treeStats.addNodeStats(current, stats);
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//if ignoreUndefined=false the miss is considered as undefined
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if (!currentNode.isIgnoreUndefined() && stats.getUndefinedCount()>0) {
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if (!currentNode.isIgnoreUndefined() && stats.undefinedCount()>0) {
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current = currentNode.getUndefined();
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}
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//if ignoreUndefined=true the miss is ignored and the score computed anyway
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@ -54,7 +58,8 @@ public class TreeProcessor {
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}
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return MatchType.parse(current);
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treeStats.setResult(MatchType.parse(current));
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return treeStats;
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}
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public double computeScore(final MapDocument doc1, final MapDocument doc2) {
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@ -72,7 +77,7 @@ public class TreeProcessor {
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score = stats.getFinalScore(currentNode.getAggregation());
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//if ignoreUndefined=false the miss is considered as undefined
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if (!currentNode.isIgnoreUndefined() && stats.getUndefinedCount()>0) {
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if (!currentNode.isIgnoreUndefined() && stats.undefinedCount()>0) {
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current = currentNode.getUndefined();
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}
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//if ignoreUndefined=true the miss is ignored and the score computed anyway
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@ -0,0 +1,51 @@
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package eu.dnetlib.pace.tree.support;
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import eu.dnetlib.pace.util.PaceException;
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import org.codehaus.jackson.map.ObjectMapper;
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import java.io.IOException;
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import java.util.HashMap;
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import java.util.Map;
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public class TreeStats {
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//<layer_id, <field:comparator, result>>
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Map<String, TreeNodeStats> stats;
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MatchType result;
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public TreeStats(){
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this.stats = new HashMap<>();
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this.result = MatchType.NO_MATCH;
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}
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public MatchType getResult(){
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return this.result;
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}
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public void setResult(MatchType result){
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this.result = result;
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}
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public Map<String, TreeNodeStats> getStats() {
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return stats;
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}
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public void setStats(Map<String, TreeNodeStats> stats) {
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this.stats = stats;
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}
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public void addNodeStats(String layerID, TreeNodeStats treeNodeStats){
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this.stats.put(layerID, treeNodeStats);
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}
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@Override
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public String toString(){
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try {
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return new ObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
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} catch (IOException e) {
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throw new PaceException("Impossible to convert to JSON: ", e);
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}
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}
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}
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@ -1,6 +1,7 @@
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package eu.dnetlib.pace.comparators;
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import eu.dnetlib.pace.clustering.NGramUtils;
|
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import eu.dnetlib.pace.tree.CityMatch;
|
||||
import eu.dnetlib.pace.tree.JaroWinklerNormalizedName;
|
||||
import eu.dnetlib.pace.config.DedupConfig;
|
||||
import org.junit.Before;
|
||||
|
@ -129,4 +130,24 @@ public class ComparatorTest extends AbstractPaceFunctions {
|
|||
|
||||
System.out.println("result = " + result);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void cityMatchTest() {
|
||||
final CityMatch cityMatch = new CityMatch(params);
|
||||
|
||||
//both names with no cities
|
||||
assertEquals(1.0, cityMatch.distance("Università", "Centro di ricerca", conf));
|
||||
|
||||
//one of the two names with no cities
|
||||
assertEquals(-1.0, cityMatch.distance("Università di Bologna", "Centro di ricerca", conf));
|
||||
|
||||
//both names with cities (same)
|
||||
assertEquals(1.0, cityMatch.distance("Universita di Bologna", "Biblioteca di Bologna", conf));
|
||||
|
||||
//both names with cities (different)
|
||||
assertEquals(0.0, cityMatch.distance("Universita di Bologna", "Universita di Torino", conf));
|
||||
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
|
|
@ -0,0 +1,23 @@
|
|||
package eu.dnetlib.pace.util;
|
||||
|
||||
import org.junit.Before;
|
||||
import org.junit.Test;
|
||||
|
||||
import java.util.HashMap;
|
||||
import java.util.Map;
|
||||
|
||||
public class UtilTest {
|
||||
|
||||
Map<String, Number> params;
|
||||
|
||||
@Before
|
||||
public void setUp(){
|
||||
params = new HashMap<String, Number>();
|
||||
}
|
||||
|
||||
@Test
|
||||
public void paceResolverTest() {
|
||||
PaceResolver paceResolver = new PaceResolver();
|
||||
paceResolver.getComparator("keywordMatch", params);
|
||||
}
|
||||
}
|
Loading…
Reference in New Issue