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