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A Learning-Based Framework for Improving Querying on Web Interfaces of Curated Knowledge Bases
2018
ACM Transactions on Internet Technology
Knowledge Bases (KBs) are widely used as one of the fundamental components in Semantic Web applications as they provide facts and relationships that can be automatically understood by machines. Curated knowledge bases usually use Resource Description Framework (RDF) as the data representation model. In order to query the RDF-presented knowledge in curated KBs, Web interfaces are built via SPARQL Endpoints. Currently, querying SPARQL Endpoints has the problems like network instability and
doi:10.1145/3155806
fatcat:gp3q4uebkvbvpky7o7kx57j22e