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SPARQL Query Recommendation by Example: Assessing the Impact of Structural Analysis on Star-Shaped Queries
Authors
Alessandro Adamou 
,
Carlo Allocca ,
Mathieu d'Aquin ,
Enrico Motta
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Volume:
2nd Conference on Language, Data and Knowledge (LDK 2019)
Series: Open Access Series in Informatics (OASIcs)
Conference: Conference on Language, Data and Knowledge (LDK) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2019-05-16
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Acknowledgements
This work was supported by the MK:Smart project (OU Ref. HGCK B4466).
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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)
https://doi.org/10.4230/OASIcs.LDK.2019.1
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.
Subject Classification
ACM Subject Classification
- Information systems → Semantic web description languages
Keywords
- SPARQL
- query recommendation
- query structure
- dataset profiling
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References
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