forked from D-Net/dnet-hadoop
added distance function fot software titles
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@ -0,0 +1,55 @@
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package eu.dnetlib.pace.distance.algo;
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import com.wcohen.ss.AbstractStringDistance;
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import eu.dnetlib.pace.distance.DistanceClass;
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import eu.dnetlib.pace.distance.SecondStringDistanceAlgo;
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import java.util.Map;
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/**
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* Compared distance between two titles, ignoring version numbers. Suitable for Software entities.
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*/
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@DistanceClass("LevensteinTitleIgnoreVersion")
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public class LevensteinTitleIgnoreVersion extends SecondStringDistanceAlgo {
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public LevensteinTitleIgnoreVersion(Map<String,Number> params){
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super(params, new com.wcohen.ss.Levenstein());
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}
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public LevensteinTitleIgnoreVersion(final double w) {
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super(w, new com.wcohen.ss.Levenstein());
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}
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protected LevensteinTitleIgnoreVersion(final double w, final AbstractStringDistance ssalgo) {
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super(w, ssalgo);
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}
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@Override
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public double distance(final String a, final String b) {
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String ca = cleanup(a);
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String cb = cleanup(b);
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ca = ca.replaceAll("\\d", "").replaceAll(getRomans(ca), "").trim();
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cb = cb.replaceAll("\\d", "").replaceAll(getRomans(cb), "").trim();
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final String cca = finalCleanup(ca);
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final String ccb = finalCleanup(cb);
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return normalize(ssalgo.score(cca, ccb), cca.length(), ccb.length());
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}
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private double normalize(final double score, final int la, final int lb) {
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return 1 - (Math.abs(score) / Math.max(la, lb));
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}
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@Override
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public double getWeight() {
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return super.weight;
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}
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@Override
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protected double normalize(final double d) {
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return 1 / Math.pow(Math.abs(d) + 1, 0.1);
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}
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}
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@ -1,6 +1,7 @@
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package eu.dnetlib.pace.distance;
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import eu.dnetlib.pace.distance.algo.JaroWinklerNormalizedName;
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import eu.dnetlib.pace.distance.algo.LevensteinTitleIgnoreVersion;
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import org.apache.commons.lang.StringUtils;
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import org.junit.Before;
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import org.junit.Test;
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@ -52,4 +53,12 @@ public class DistanceAlgoTest extends AbstractPaceFunctions {
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System.out.println(result);
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}
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@Test
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public void testLevensteinTitleIgnoreVersion() {
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final LevensteinTitleIgnoreVersion algo = new LevensteinTitleIgnoreVersion(params);
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double result = algo.distance("gCube data layer v1.0 XI", "gCube data layer v1.5 VIII");
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System.out.println(result);
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}
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}
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