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DOI: 10.4230/OASIcs.LDK.2019.1
SPARQL Query Recommendation by Example: Assessing the Impact of Structural Analysis on Star-Shaped Queries

Authors: Alessandro Adamou, Carlo Allocca, Mathieu d'Aquin, and Enrico Motta

Published in: OASIcs, Volume 70, 2nd Conference on Language, Data and Knowledge (LDK 2019)

Abstract
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.
Cite as

Alessandro Adamou, Carlo Allocca, Mathieu d'Aquin, and Enrico Motta. SPARQL Query Recommendation by Example: Assessing the Impact of Structural Analysis on Star-Shaped Queries. In 2nd Conference on Language, Data and Knowledge (LDK 2019). Open Access Series in Informatics (OASIcs), Volume 70, pp. 1:1-1:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{adamou_et_al:OASIcs.LDK.2019.1,
  author =	{Adamou, Alessandro and Allocca, Carlo and d'Aquin, Mathieu and Motta, Enrico},
  title =	{{SPARQL Query Recommendation by Example: Assessing the Impact of Structural Analysis on Star-Shaped Queries}},
  booktitle =	{2nd Conference on Language, Data and Knowledge (LDK 2019)},
  pages =	{1:1--1:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-105-4},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{70},
  editor =	{Eskevich, Maria and de Melo, Gerard and F\"{a}th, Christian and McCrae, John P. and Buitelaar, Paul and Chiarcos, Christian and Klimek, Bettina and Dojchinovski, Milan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2019.1},
  URN =		{urn:nbn:de:0030-drops-103651},
  doi =		{10.4230/OASIcs.LDK.2019.1},
  annote =	{Keywords: SPARQL, query recommendation, query structure, dataset profiling}
}
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