Publication | Open Access
Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO
340
Citations
24
References
2017
Year
Suitable KgEngineeringKnowledge ExtractionSemantic WebText MiningKnowledge Graph EmbeddingsInformation RetrievalData ScienceData MiningMetadata QualityData IntegrationLinked DataData ManagementKnowledge DiscoveryData QualityKnowledge GraphsDatabase TechnologyData Quality CriteriaKnowledge BaseKnowledge Data EngineeringBusinessKnowledge ManagementSemantic GraphAvailable Knowledge GraphsBig Data
Large, cross‑domain knowledge graphs such as DBpedia, Freebase, OpenCyc, Wikidata, and YAGO have been created but lack an in‑depth comparative analysis. This survey defines data‑quality criteria to analyze and compare these knowledge graphs. It also proposes a framework to identify the most suitable knowledge graph for a given setting.
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 pro vide 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.
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