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− | |Referiert= | + | |Referiert=Ja |
|Title=Linked Data Quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO | |Title=Linked Data Quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO | ||
− | |Year= | + | |Year=2018 |
|Journal=Semantic Web Journal | |Journal=Semantic Web Journal | ||
+ | |Volume=9 | ||
+ | |Number=2 | ||
+ | |Pages=77–129 | ||
|Publisher=IOS Press | |Publisher=IOS Press | ||
+ | |Note=https://dblp.org/rec/bibtex/journals/semweb/FarberBMR18 | ||
}} | }} | ||
{{Publikation Details | {{Publikation Details | ||
|Abstract=In recent years, several noteworthy large, cross-domain and openly available knowledge graphs (KGs) have been created. These include DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. Although extensively in use, these KGs have not been subject to an in-depth comparison so far. In this survey, we provide data quality criteria according to which KGs can be analyzed and analyze and compare the above mentioned KGs. Furthermore, we propose a framework for finding the most suitable KG for a given setting. | |Abstract=In recent years, several noteworthy large, cross-domain and openly available knowledge graphs (KGs) have been created. These include DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. Although extensively in use, these KGs have not been subject to an in-depth comparison so far. In this survey, we provide data quality criteria according to which KGs can be analyzed and analyze and compare the above mentioned KGs. Furthermore, we propose a framework for finding the most suitable KG for a given setting. | ||
− | |Forschungsgruppe=Web Science | + | |Download=KG-Comparison-SWJ2017.pdf |
+ | |Link=http://km.aifb.kit.edu/sites/knowledge-graph-comparison/ | ||
+ | |DOI Name=10.3233/SW-170275 | ||
+ | |Projekt=SUITE, XLiMe | ||
+ | |Forschungsgruppe=Web Science | ||
}} | }} | ||
{{Forschungsgebiet Auswahl | {{Forschungsgebiet Auswahl | ||
|Forschungsgebiet=Wissensrepräsentation | |Forschungsgebiet=Wissensrepräsentation | ||
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+ | {{Forschungsgebiet Auswahl | ||
+ | |Forschungsgebiet=Ontologiemodellierung | ||
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+ | {{Forschungsgebiet Auswahl | ||
+ | |Forschungsgebiet=Semantic Web | ||
+ | }} | ||
+ | {{Forschungsgebiet Auswahl | ||
+ | |Forschungsgebiet=Semantic Web Infrastructure | ||
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Aktuelle Version vom 17. November 2019, 16:15 Uhr
Linked Data Quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO
Linked Data Quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO
Veröffentlicht: 2018
Journal: Semantic Web Journal
Nummer: 2
Seiten: 77–129
Verlag: IOS Press
Volume: 9
Bemerkung: https://dblp.org/rec/bibtex/journals/semweb/FarberBMR18
Referierte Veröffentlichung
Kurzfassung
In recent years, several noteworthy large, cross-domain and openly available knowledge graphs (KGs) have been created. These include DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. Although extensively in use, these KGs have not been subject to an in-depth comparison so far. In this survey, we provide data quality criteria according to which KGs can be analyzed and analyze and compare the above mentioned KGs. Furthermore, we propose a framework for finding the most suitable KG for a given setting.
Download: Media:KG-Comparison-SWJ2017.pdf
Weitere Informationen unter: Link
DOI Link: 10.3233/SW-170275
Wissensrepräsentation, Semantic Web Infrastructure, Ontologiemodellierung, Semantic Web