@inproceedings{930ad73d257e40559eb50ec258b0468c,
title = "Interactive inference of sparql queries using provenance",
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.",
keywords = "Provenance, SPARQL",
author = "Efrat Abramovitz and Daniel Deutch and Amir Gilad",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; null ; Conference date: 16-04-2018 Through 19-04-2018",
year = "2018",
month = oct,
day = "24",
doi = "10.1109/ICDE.2018.00059",
language = "אנגלית",
series = "Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "581--592",
booktitle = "Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018",
address = "ארצות הברית",
}