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A query language for semantic complex event processing: Syntax, semantics and implementation

Abstract : The field of Complex Event Processing (CEP) deals with the techniques and tools developed to efficiently process pattern-based queries over data streams. The Semantic Web, through its standards and technologies, is in constant pursuit to provide solutions for such paradigm while employing the RDF data model. The integration of Semantic Web technologies in this context can handle the heterogeneity, integration and interpretation of data streams at the semantic level. In this paper, we propose and implement a new query language, called SPAseq, that extends SPARQL with new Semantic Complex Event Processing (SCEP) operators that can be evaluated over RDF graph-based events. The novelties of SPAseq include (i) the separation of general graph pattern matching constructs and temporal operators; (ii) the support for RDF graph-based events and multiple RDF graph streams; (iii) the expressibility of temporal operators such as Kleene+, conjunction, disjunction and event selection strategies; and (iv) the operators to integrate background information and streaming RDF graph streams. Hence, SPAseq enjoys good expressiveness compared with the existing solutions. Furthermore, we provide an efficient implementation of SPAseq using a non-deterministic automata (NFA) model for an efficient evaluation of the SPAseq queries. We provide the syntax and semantics of SPAseq and based on this, we show how it can be implemented in an efficient manner. Moreover, we also present an experimental evaluation of its performance, showing that it improves over state-of-the-art approaches.
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Contributor : Florent Breuil <>
Submitted on : Friday, August 24, 2018 - 3:52:57 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:10 PM



Syed Gillani, Antoine Zimmermann, Gauthier Picard, Frederique Laforest. A query language for semantic complex event processing: Syntax, semantics and implementation. Semantic Web – Interoperability, Usability, Applicability, IOS Press, 2019, 10 (1), pp.53-93. ⟨10.3233/SW-180313⟩. ⟨hal-01861610⟩



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