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pro vyhledávání: '"Cheon, Heeseon"'
To effectively manage and utilize knowledge graphs, it is crucial to have metrics that can assess the quality of knowledge graphs from various perspectives. While there have been studies on knowledge graph quality metrics, there has been a lack of re
Externí odkaz:
http://arxiv.org/abs/2411.06385
This work presents six structural quality metrics that can measure the quality of knowledge graphs and analyzes five cross-domain knowledge graphs on the web (Wikidata, DBpedia, YAGO, Google Knowledge Graph, Freebase) as well as 'Raftel', Naver's int
Externí odkaz:
http://arxiv.org/abs/2211.10011