Provenance-Based SPARQL Query Formulation

Yael Amsterdamer, Yehuda Callen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We present in this paper a novel solution for assisting users in formulating SPARQL queries. The high-level idea is that users write “semi-formal SPARQL queries”, namely, queries whose structure resembles SPARQL but are not necessarily grounded to the schema of the underlying Knowledge Base (KB) and require only basic familiarity with SPARQL. This means that the user-intended query over the KB may differ from the specified semi-formal query in its structure and query elements. We design a novel framework that systematically and gradually refines the query to obtain candidate formal queries that do match the KB. Crucially, we introduce a formal notion of provenance tracking this query refinement process, and use the tracked provenance to prompt the user for fine-grained feedback on parts of the candidate query, guiding our search. Experiments on a diverse query workload with respect to both DBpedia and YAGO show the usefulness of our approach.

Original languageEnglish
Title of host publicationDatabase and Expert Systems Applications - 33rd International Conference, DEXA 2022, Proceedings
EditorsChristine Strauss, Alfredo Cuzzocrea, Gabriele Kotsis, Ismail Khalil, A Min Tjoa
PublisherSpringer Science and Business Media Deutschland GmbH
Pages116-129
Number of pages14
ISBN (Print)9783031124228
DOIs
StatePublished - 2022
Event33rd International Conference on Database and Expert Systems Applications, DEXA 2022 - Vienna, Austria
Duration: 22 Aug 202224 Aug 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13426 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference33rd International Conference on Database and Expert Systems Applications, DEXA 2022
Country/TerritoryAustria
CityVienna
Period22/08/2224/08/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Funding

Acknowledgements. This work was partly funded by the Israel Science Foundation (grant No. 2015/21) and by the Israel Ministry of Science and Technology.

FundersFunder number
Israel Science Foundation2015/21
Ministry of science and technology, Israel

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