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[Author Merger DoiBoost] add last part to consider also author->enrich map

This commit is contained in:
Miriam Baglioni 2021-11-19 18:18:46 +01:00
parent f100dc5880
commit 1dd15ee2f2
1 changed files with 46 additions and 6 deletions
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52
dhp-workflows/dhp-doiboost/src/main/java/eu/dnetlib/doiboost/DoiBoostAuthorMerger.java
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@ -94,8 +94,6 @@ public class DoiBoostAuthorMerger {
//valutare se questa cosa va invertita: dovrei prendere per ogni enriching author quello che piu' gli somiglia //valutare se questa cosa va invertita: dovrei prendere per ogni enriching author quello che piu' gli somiglia
//nella base list non il contrario //nella base list non il contrario
private static void enrichPidFromList(List<Author> base, List<Author> enrich) { private static void enrichPidFromList(List<Author> base, List<Author> enrich) {
//search authors having identifiers in the enrich list //search authors having identifiers in the enrich list
@ -110,7 +108,7 @@ public class DoiBoostAuthorMerger {
a -> new Tuple2<>(DHPUtils.md5(a.getFullname()), AuthorAssoc.newInstance(a))) a -> new Tuple2<>(DHPUtils.md5(a.getFullname()), AuthorAssoc.newInstance(a)))
.collect(Collectors.toMap(Tuple2::_1, Tuple2::_2, (x1, x2) -> x1)); .collect(Collectors.toMap(Tuple2::_1, Tuple2::_2, (x1, x2) -> x1));
Map<String, Tuple2<List<String>, Double>> baseAssoc = new HashMap<>(); Map<String, Tuple2<String,Tuple2<List<String>, Double>>> baseAssoc = new HashMap<>();
//for each author in the base list, we search the best enriching match //for each author in the base list, we search the best enriching match
@ -124,7 +122,8 @@ public class DoiBoostAuthorMerger {
.collect(Collectors.toList())) .collect(Collectors.toList()))
) )
.forEach(t2 -> { .forEach(t2 -> {
String base_name = DHPUtils.md5(t2._1().getFullname()); String base_name = t2._1().getFullname();
String base_name_md5 = DHPUtils.md5(t2._1().getFullname());
Double max_score = 0.0; Double max_score = 0.0;
List<String> enrich_name = new ArrayList(); List<String> enrich_name = new ArrayList();
for (Tuple2<Author, Double> t : t2._2()) { for (Tuple2<Author, Double> t : t2._2()) {
@ -149,12 +148,53 @@ public class DoiBoostAuthorMerger {
} }
} }
if(max_score > 0){ if(max_score > 0){
baseAssoc.put(base_name, new Tuple2<>(enrich_name, max_score)); baseAssoc.put(base_name_md5, new Tuple2(base_name, new Tuple2<>(enrich_name, max_score)));
} }
}); });
List<Tuple2<Double, Tuple2<String, List<String>>>> list = baseAssoc.keySet().stream().map(k -> {
Tuple2<String, Tuple2<List<String>, Double>> map_entry = baseAssoc.get(k);
return new Tuple2<>(map_entry._2()._2(), new Tuple2<>(map_entry._1(), map_entry._2()._1()));
})
.collect(Collectors.toList());
list.sort(Comparator.comparing(e -> e._1()));
//ordino per max score la baseAssoc
for (int i = list.size() -1 ; i>=0 ; i-- ){
Tuple2<Double, Tuple2<String, List<String>>> tmp = list.get(i);
List<String> entries = tmp._2()._2();
//se len = 1 => ho un solo e che con questo a ha max score
if(entries.size() == 1){
if(assocMap.containsKey(entries.get(0))) {
enrichAuthor(assocMap.get(entries.get(0)));
assocMap.remove(entries.get(0));
}
}else{
String author_fullname = tmp._2()._1();
long commonWords = 0;
String enriching = null;
for(String entry : entries){
if (assocMap.containsKey(entry)){
long words = getCommonWords(normalize(entry),
normalize(author_fullname));
if (words > commonWords){
commonWords = words;
enriching = entry;
}
if(words == commonWords){
enriching = null;
}
}
assocMap.keySet().forEach(k -> enrichAuthor(assocMap.get(k))); }
if(enriching != null){
enrichAuthor(assocMap.get(entries.get(0)));
assocMap.remove(entries.get(0));
}
//TODO pensare ad un modo per arricchire con il miglior e questo autore
//Siamo nel caso in cui un autore ha piu' di un e con lo stesso similarity score
}
}
// assocMap.keySet().forEach(k -> enrichAuthor(assocMap.get(k)));
} }