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Research on Complex Event Detection Method Based on Syntax Tree

  • Wenjun YangEmail author
  • Aizhang Guo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 891)

Abstract

This paper focuses on the diversity of event flows and the limitation of memory. In this paper, an application tree structure is proposed to compress event storage, and a complex event detection method based on syntax tree is adopted. This method uses the strategy of constraint downshift and shared subsequence to achieve the goal of saving time and space. Constraint downshift prioritizes events with low pass rates and eliminates a large number of non-compliant events, thereby increasing efficiency. The shared subsequence is based on the existing matching results, and a new result sequence is constructed according to the query event pattern. In order to improve query efficiency and save storage space, nested queries are used to query complex events. The effectiveness of these methods was verified by experiments with these strategies, and the accuracy of the method was compared with the SASE method for complex event detection. Finally, summarize the paper and point out the next research direction.

Keywords

Syntax tree Complex event detection Shared subsequence Constraint down 

Notes

Acknowledgement

This work was supported by Key Research and Development Plan of Shandong Province (2017GGX201001).

References

  1. 1.
    Hu, C., Li, P.: Comparison of MES between productions of continuous industries and discrete industries. Control Instrum. Chem. Ind. 30(5), 1–4 (2003)Google Scholar
  2. 2.
    Wang, F., Liu, S., Liu, P.: Complex RFID event processing. Int. J. Very Large Data Bases 18(4), 913–931 (2009).  https://doi.org/10.1007/s00778-009-0139-0MathSciNetCrossRefGoogle Scholar
  3. 3.
    Dimitriadou, K., Papaemmanouil, O.: Explore-by-example: an automatic query steering framework for interactive data exploration. In: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data Snowbird, USA, pp. 517–528 (2014).  https://doi.org/10.1145/2588555.2610523
  4. 4.
    Yi, H.: Research on reconfigurable manufacturing execution system for RFID-based real-time monitoring. Tsinghua University, (2011)Google Scholar
  5. 5.
    Liu, H.-L., Li, F.-F.: Processing nested query over event streams with uncertain timestamps. Chin. J. Comput., 123–134 (2016).  https://doi.org/10.13190/j.jbupt.2017.02.008
  6. 6.
    Wang, Y., Mend, Y.: Method of complex events detection based on shared matching results. Appl. Res. Comput., 2338–2341 (2014).  https://doi.org/10.3969/j.i55n.1001-3695.2014.08.023
  7. 7.
    Shahbaz, M., McMinn, P., Stevenson, M.: Automatic generation of valid and invalid test data for string validation routines using web searches and regular expressions. Sci. Comput. Program. 97, 405–425 (2015).  https://doi.org/10.1016/j.scico.2014.04.008CrossRefGoogle Scholar
  8. 8.
    Wasserkrug, S., Gal, A.: Efficient processing of uncertain events in rule-based systems. IEEE Trans. Knowl. Data Eng. 24(1), 45–58 (2012).  https://doi.org/10.1109/TKDE.2010.204CrossRefGoogle Scholar
  9. 9.
    Gyllstrom, D., Wu, E., Chae, H.J., et al.: SASE: complex event processing over streams. arXiv preprint arXiv:cs/0612128 (2006)

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Qilu University of Technology (Shandong Academy of Sciences)JinanChina

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