Abstract
The task of accessing knowledge graphs through structured query languages like SPARQL is rather demanding for ordinary users. Consequently, there are various approaches that attempt to exploit the simpler and widely used keyword-based search paradigm, either by translating keyword queries to structured queries, or by adopting classical information retrieval (IR) techniques. This paper demonstrates Elas4RDF, a keyword search system over RDF that is based on Elasticsearch, an out-of-the-box document-centric IR system. Elas4RDF indexes and retrieves triples (instead of entities), and thus yields more refined and informative results, that can be viewed through different perspectives. In this paper we demonstrate the performance of the Elas4RDF system in queries of various types, and showcase the benefits from offering different perspectives for aggregating and visualising the search results.
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Acknowledgements
This work has received funding from the European Union’s Horizon 2020 innovation action BlueCloud (Grant agreement No 862409).
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Kadilierakis, G., Nikas, C., Fafalios, P., Papadakos, P., Tzitzikas, Y. (2020). Elas4RDF: Multi-perspective Triple-Centered Keyword Search over RDF Using Elasticsearch. In: Harth, A., et al. The Semantic Web: ESWC 2020 Satellite Events. ESWC 2020. Lecture Notes in Computer Science(), vol 12124. Springer, Cham. https://doi.org/10.1007/978-3-030-62327-2_21
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DOI: https://doi.org/10.1007/978-3-030-62327-2_21
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