GoRelations: Towards an Intuitive Query System for RDF Data

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Users need better ways to explore DBpedia and obtain information from it. Using SPARQL requires not only mastering its syntax and semantics but also understanding the RDF data model, the ontology used by the DBpedia, and URIs for entities of interest. Natural language question answering systems solve the problem, but these are still subjects of research. We describe a compromise in which non-experts specify a graphical “skeleton” for a query and annotate it with freely chosen words, phrases and entity names. The combination reduces ambiguity and allows us to reliably produce an interpretation that can be translated into SPARQL. We demonstrate the approach’s feasibility with an implementation that performs well in an evaluation using queries from the 2011 QALD workshop. Key contributions are the robust methods that combine statistical association and semantic similarity to map user terms to the most appropriate classes and properties used in the DBpedia ontology.


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intuitive query, ontology mapping, semantic similarity, semantic web, statistical association

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University of Maryland, Baltimore County

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Past Projects

  1. Graph of Relations