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Authors: Mohamed Kharrat ; Anis Jedidi and Faiez Gargouri

Affiliation: University of Sfax, Tunisia

Keyword(s): SPARQL, Queries, RDF.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Context Discovery ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Multimedia Data ; Pre-Processing and Post-Processing for Data Mining ; Structured Data Analysis and Statistical Methods ; Symbolic Systems

Abstract: Data retrieval is becoming more difficult due to the heterogeneity and the huge amount of Data flowing in the Web. On the other hand, novice users could not handle querying languages (e.g., SPARQL) or knowledge based techniques. To simplify querying process, we introduce in this paper, a proposal of automatic SPARQL query generation based on user-supplied keywords. The construction of a SPARQL query is based on the top relevant RDF sub-graph, selected from our RDF Triplestore. This latter rely on our defined semantic network and on our Contextual Schema both published in two different papers of our previous studies. We evaluate 50 queries by using three measures. Results show an F-Score of about 50%. This proposal is already implemented as a web interface and the whole queries interpretation and processing is performed over this interface.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Kharrat, M.; Jedidi, A. and Gargouri, F. (2016). SPARQL Query Generation based on RDF Graph. In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR; ISBN 978-989-758-203-5; ISSN 2184-3228, SciTePress, pages 450-455. DOI: 10.5220/0006091904500455

@conference{kdir16,
author={Mohamed Kharrat. and Anis Jedidi. and Faiez Gargouri.},
title={SPARQL Query Generation based on RDF Graph},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR},
year={2016},
pages={450-455},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006091904500455},
isbn={978-989-758-203-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR
TI - SPARQL Query Generation based on RDF Graph
SN - 978-989-758-203-5
IS - 2184-3228
AU - Kharrat, M.
AU - Jedidi, A.
AU - Gargouri, F.
PY - 2016
SP - 450
EP - 455
DO - 10.5220/0006091904500455
PB - SciTePress