License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2019.1
URN: urn:nbn:de:0030-drops-103651
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2019/10365/
Adamou, Alessandro ;
Allocca, Carlo ;
d'Aquin, Mathieu ;
Motta, Enrico
SPARQL Query Recommendation by Example: Assessing the Impact of Structural Analysis on Star-Shaped Queries
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.
BibTeX - Entry
@InProceedings{adamou_et_al:OASIcs:2019:10365,
author = {Alessandro Adamou and Carlo Allocca and Mathieu d'Aquin and Enrico Motta},
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 = {OpenAccess Series in Informatics (OASIcs)},
ISBN = {978-3-95977-105-4},
ISSN = {2190-6807},
year = {2019},
volume = {70},
editor = {Maria Eskevich and Gerard de Melo and Christian F{\"a}th and John P. McCrae and Paul Buitelaar and Christian Chiarcos and Bettina Klimek and Milan Dojchinovski},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2019/10365},
URN = {urn:nbn:de:0030-drops-103651},
doi = {10.4230/OASIcs.LDK.2019.1},
annote = {Keywords: SPARQL, query recommendation, query structure, dataset profiling}
}
Keywords: |
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SPARQL, query recommendation, query structure, dataset profiling |
Collection: |
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2nd Conference on Language, Data and Knowledge (LDK 2019) |
Issue Date: |
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2019 |
Date of publication: |
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16.05.2019 |