Interactive inference of sparql queries using provenance

Efrat Abramovitz, Daniel Deutch, Amir Gilad

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

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 languageEnglish
Title of host publicationProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages581-592
Number of pages12
ISBN (Electronic)9781538655207
DOIs
StatePublished - 24 Oct 2018
Event34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France
Duration: 16 Apr 201819 Apr 2018

Publication series

NameProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

Conference

Conference34th IEEE International Conference on Data Engineering, ICDE 2018
Country/TerritoryFrance
CityParis
Period16/04/1819/04/18

Keywords

  • Provenance
  • SPARQL

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