Skip to main content
SpringerLink
Log in

The Semantic Complex Event Processing Based on Metagraph Approach

  • Conference paper
  • First Online:
Biologically Inspired Cognitive Architectures 2019 (BICA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 948))

Included in the following conference series:

Abstract

In this paper, the features of semantic complex event processing (SCEP) approach based on the metagraph model is considered. The idea of event and event processing is one of the fundamental ideas in the fields of complex systems and software engineering. The definitions and descriptions of Complex Event Processing (CEP) and semantic complex event processing (SCEP) are reviewed and summed up. Semantic Web technologies are typically used for semantics description in SCEP approach. Complex event processing combines data from multiple sources. Complex event processing engine may include several processing levels, and semantic complex events may be enriched during processing. The goal of complex event processing is to identify meaningful events (such as opportunities or threats) in the form of the complex situation. Complex event processing engine may use global ontology and static and dynamic semantics. The RDF approach has limitations in describing complex situations, while the metagraph approach addresses RDF limitations in a natural way without emergence loss. The metagraph model is used as a unified model for semantic events description (static and dynamic semantics), complex situation description, global ontology description. Using the combination of the metagraph data model and metagraph agents model it is possible to construct the complex semantic event processing engine in the form of the hierarchy of dynamic metagraph agents.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Chandy Mani K (2006): Event-driven applications: costs, benefits and design approaches. Gartner application integration and web services summit 2006

    Google Scholar 

  2. Ushakov V, Samsonovich A (2015) Toward a BICA-model-based study of cognition using brain imaging techniques. Procedia Comput Sci 71:254–264

    Article  Google Scholar 

  3. Choi D, Langley P (2018) Evolution of the icarus cognitive architecture. Cognitive Syst Res 48:25–38

    Article  Google Scholar 

  4. Luckham D (2012) Event processing for business: organizing the real-time enterprise. John Wiley & Sons, Hoboken

    Book  Google Scholar 

  5. van der Aalst W (2016) Process mining: data science in action. Springer, Berlin

    Book  Google Scholar 

  6. Keskisarkka R (2014): Semantic complex event processing for decision support. In: Proceedings of 13th international semantic web conference – ISWC 2014, pp. 529–536. Springer, Riva del Garda, Italy

    Chapter  Google Scholar 

  7. Zhou Q, Simmhan Y, Prasanna V (2017) Knowledge-infused and consistent complex event processing over real-time and persistent streams. Future Gener Comput Syst 76:391–406. https://doi.org/10.1016/j.future.2016.10.030

    Article  Google Scholar 

  8. Teymourian K (2016) Knowledge-based complex event processing: concepts and implementation. Südwestdeutscher Verlag für Hochschulschriften, Saarbrücken

    Google Scholar 

  9. Basu A, Blanning R (2007) Metagraphs and their applications. Springer, New York

    MATH  Google Scholar 

  10. Chernenkiy V, Gapanyuk Yu, Nardid A, Gushcha A, Fedorenko Yu (2017) The hybrid multidimensional-ontological data model based on metagraph approach. In: Petrenko A, Voronkov A (eds) Perspectives of system informatics, LNCS, vol 10742. Springer, Moscow, pp 72–87

    Chapter  Google Scholar 

  11. Defining N-ary Relations on the Semantic Web. W3C Working Group Note 12 April 2006. http://www.w3.org/TR/swbp-n-aryRelations. Accessed 06 May 2019

  12. Chernenkiy V, Gapanyuk Yu, Nardid A, Skvortsova M, Gushcha A, Fedorenko Yu, Picking R (2017): Using the metagraph approach for addressing RDF knowledge representation limitations. In: Proceedings of internet technologies and applications (ITA’ 2017), Wrexham, United Kingdom, pp. 47–52

    Google Scholar 

  13. Lieto A, Lebiere C, Oltramari A (2018) The knowledge level in cognitive architectures: Current limitations and possible developments. Cognitive Syst Res 48:39–55

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Bauman Moscow State Technical University, Baumanskaya 2-Ya, 5, 105005, Moscow, Russia

    Yuriy E. Gapanyuk

Authors
  1. Yuriy E. Gapanyuk
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuriy E. Gapanyuk .

Editor information

Editors and Affiliations

  1. Moscow Engineering Physics Institute (MEPhI), Department of Cybernetics, National Research Nuclear University (NRNU), Moscow, Russia

    Alexei V. Samsonovich

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gapanyuk, Y.E. (2020). The Semantic Complex Event Processing Based on Metagraph Approach. In: Samsonovich, A. (eds) Biologically Inspired Cognitive Architectures 2019. BICA 2019. Advances in Intelligent Systems and Computing, vol 948. Springer, Cham. https://doi.org/10.1007/978-3-030-25719-4_13

Download citation

Publish with us

Policies and ethics

Search

Navigation