Comparing DBpedia, Wikidata, and YAGO for Web Information Retrieval
- 350 Downloads
Knowledge graphs serve as the primary sources of structured data in many Semantic Web applications. In this paper, the three most popular cross-domain knowledge graphs (KGs), namely, DBpedia, YAGO, and Wikidata were empirically explored and compared. These knowledge graphs were compared from the perspectives of completeness of the relations, timeliness of the data and accessibility of the KG. Three fundamental categories of named entities were queried within the KGs for detailed analysis of the data returned. From the experimental results and findings, Wikidata scores the highest in term of the timeliness of the data provided owing to the effort of global community update, with DBpedia LIVE being the next. Regarding accessibility, it was observed that DBpedia and Wikidata gave continuous access using public SPARQL endpoint, while YAGO endpoints were intermittently inaccessible. With respect to completeness of predicates, none of the KGs have a remarkable lead for any of the selected categories. From the analysis, it is observed that none of the KG can be considered complete on its own with regard to the relations of an entity.
KeywordsSemantic web Knowledge graphs DBpedia YAGO Wikidata
This work is partially funded by Fundamental Research Grant Scheme (FRGS) by Malaysia Ministry of Higher Education (Ref: FRGS/1/2017/ICT02/MMU/02/6).
- 1.Tim B, Lee B, Hendler J, Lassila O (2001) The semantic web will enable machines to comprehend semantic documents, no. May, pp 1–5Google Scholar
- 2.Bizer C et al (2008) Linked data on the web. WWW2008 Work. Linked Data Web, pp 1265–1266Google Scholar
- 3.Zaveri A, Kontokostas D, Leipzig U, Hellmann S (2017) Linked data quality of DBpedia, freebase Semant. Web, 0(0):1–53Google Scholar
- 5.Li TRBY, Wang H, Zhao L (2016) The semantic web. Latest advances and new domains 9678:52–68Google Scholar
- 6.Paulheim H (2015) Knowledge graph refinement: a survey of approaches and evaluation methods. Semant. Web, 0:1–0Google Scholar
- 9.Hoffart J, Suchanek FM, Berberich K, Weikum G (2013) YAGO2: a spatially and temporally enhanced knowledge base from Wikipedia. IJCAI Int Jt Conf Artif Intell 3161–3165Google Scholar
- 10.Demner-Fushman D et al (2013) YAGO3 : a knowledge base from multilingual wikipedia. J Biomed Inform 46(SUPPL):129–132Google Scholar
- 12.Verborgh R et al (2014) Querying datasets on the web with high availability. Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics) 8796(Iswc 2014):180–196Google Scholar
- 13.Voigt M, Mitschick A, Schulz J (2012) Yet another triple store benchmark? Practical experiences with real-world data. CEUR Workshop Proc, 912(Sda):85–94Google Scholar