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 graph and require only basic familiarity with SPARQL. This means that the user-intended query over the knowledge graph 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 knowledge graph. 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 language | English |
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Pages (from-to) | 2165-2191 |
Number of pages | 27 |
Journal | Knowledge and Information Systems |
Volume | 66 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2024 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023.
Funding
This work was partly funded by the Israel Science Foundation (grant No. 2015/21) and by the Israel Ministry of Science and Technology.
Funders | Funder number |
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Israel Science Foundation | 2015/21 |
Ministry of science and technology, Israel |
Keywords
- Data exploration
- Knowledge graph
- Provenance
- SPARQL