Abstract
Grounded on real industrial use cases, we recently proposed an ontology-based visual query system for SPARQL, named OptiqueVQS. Ontology-based visual query systems employ ontologies and visual representations to depict the domain of interest and queries, and are promising to enable end users without any technical background to access data on their own. However, even with considerably small ontologies, the number of ontology elements to choose from increases drastically, and hence hinders usability. Therefore, in this paper, we propose a method using the log of past queries for ranking and suggesting query extensions as a user types a query, and identify emerging issues to be addressed.
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Soylu, A., Giese, M., Jimenez-Ruiz, E., Kharlamov, E., Zheleznyakov, D., Horrocks, I. (2014). Towards Exploiting Query History for Adaptive Ontology-Based Visual Query Formulation. In: Closs, S., Studer, R., Garoufallou, E., Sicilia, MA. (eds) Metadata and Semantics Research. MTSR 2014. Communications in Computer and Information Science, vol 478. Springer, Cham. https://doi.org/10.1007/978-3-319-13674-5_11
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DOI: https://doi.org/10.1007/978-3-319-13674-5_11
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