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  • Titel: SPARQL Query Recommendation by Example: Assessing the Impact of Structural Analysis on Star-Shaped Queries
  • Beteiligte: Adamou, Alessandro [Verfasser:in]; Allocca, Carlo [Verfasser:in]; d'Aquin, Mathieu [Verfasser:in]; Motta, Enrico [Verfasser:in]
  • Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2019
  • Sprache: Englisch
  • DOI: https://doi.org/10.4230/OASIcs.LDK.2019.1
  • Schlagwörter: SPARQL ; query recommendation ; query structure ; dataset profiling
  • Entstehung:
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  • Beschreibung: One of the existing query recommendation strategies for unknown datasets is "by example", i.e. based on a query that the user already knows how to formulate on another dataset within a similar domain. In this paper we measure what contribution a structural analysis of the query and the datasets can bring to a recommendation strategy, to go alongside approaches that provide a semantic analysis. Here we concentrate on the case of star-shaped SPARQL queries over RDF datasets. The illustrated strategy performs a least general generalization on the given query, computes the specializations of it that are satisfiable by the target dataset, and organizes them into a graph. It then visits the graph to recommend first the reformulated queries that reflect the original query as closely as possible. This approach does not rely upon a semantic mapping between the two datasets. An implementation as part of the SQUIRE query recommendation library is discussed.
  • Zugangsstatus: Freier Zugang