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Distributed Reasoning of RDF Data

Authors :
Raghava Mutharaju
Irini Fundulaki
Danh Le Phuoc
Sherif Sakr
Marcin Wylot
Source :
Linked Data ISBN: 9783319735146
Publication Year :
2018
Publisher :
Springer International Publishing, 2018.

Abstract

Large RDF interconnected datasets, especially in the form of open as well as enterprise knowledge graphs, are constructed and consumed in several domains. Reasoning over such large knowledge graphs poses several performance challenges. In practice, although there has been some prior work on scalable approaches to RDF reasoning, the interest in this field started gathering momentum with the rising popularity of modern big data processing systems (e.g., Hadoop, Spark). In this chapter, we cover five main categories of distributed RDF reasoning systems: (1) Peer-to-Peer RDF reasoning systems, (2) NoSQL-based RDF reasoning systems, (3) Hadoop-based RDF reasoning systems, (4) Spark-based RDF reasoning systems, and (5) shared memory RDF reasoning systems.

Details

ISBN :
978-3-319-73514-6
ISBNs :
9783319735146
Database :
OpenAIRE
Journal :
Linked Data ISBN: 9783319735146
Accession number :
edsair.doi...........3fd6ead49d0d7985a0242e66abd78da1
Full Text :
https://doi.org/10.1007/978-3-319-73515-3_6