Predicting SPARQL Query Performance and Explaining Linked Data

Rakebul Hasan 1, *
* Corresponding author
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : As the complexity of the Semantic Web increases, efficient ways to query the Semantic Web data is becoming increasingly impor-tant. Moreover, consumers of the Semantic Web data may need expla-nations for debugging or understanding the reasoning behind producing the data. In this paper, firstly we address the problem of SPARQL query performance prediction. Secondly we discuss how to explain Linked Data in a decentralized fashion. Finally we discuss how to summarize the ex-planations.
Document type :
Conference papers
Complete list of metadatas

Cited literature [28 references]  Display  Hide  Download

https://hal.inria.fr/hal-01075488
Contributor : Rakebul Hasan <>
Submitted on : Friday, October 17, 2014 - 5:03:28 PM
Last modification on : Monday, November 5, 2018 - 3:52:09 PM
Long-term archiving on : Sunday, January 18, 2015 - 10:46:41 AM

File

eswc2014-dc.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Rakebul Hasan. Predicting SPARQL Query Performance and Explaining Linked Data. 11th Extended Semantic Web Conference (ESWC2014), May 2014, Crete, Greece. pp.795 - 805, ⟨10.1007/978-3-319-07443-6_53⟩. ⟨hal-01075488⟩

Share

Metrics

Record views

291

Files downloads

215