Abstract
Inference of queries from their output examples has been extensively studied in multiple contexts as means to ease the formulation of queries. In this paper we propose a novel approach for the problem, based on provenance. The idea is to use provenance in two manners: first as an additional information that is associated with the given examples and explains their rationale; and then again as a way to show users a description of the difference between candidate queries, prompting their feedback. We have implemented the framework in the context of simple graph patterns and union thereof, and demonstrate its effectiveness in the context of multiple ontologies.
Original language | English |
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Title of host publication | Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 581-592 |
Number of pages | 12 |
ISBN (Electronic) | 9781538655207 |
DOIs | |
State | Published - 24 Oct 2018 |
Externally published | Yes |
Event | 34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France Duration: 16 Apr 2018 → 19 Apr 2018 |
Publication series
Name | Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018 |
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Conference
Conference | 34th IEEE International Conference on Data Engineering, ICDE 2018 |
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Country/Territory | France |
City | Paris |
Period | 16/04/18 → 19/04/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- Provenance
- SPARQL