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Cluster Computing

, Volume 22, Supplement 4, pp 9571–9579 | Cite as

Research of the processing technology for time complex event based on LSTM

  • Qing Li
  • Jiang ZhongEmail author
  • Yongqin Tao
  • Lili Li
  • Xiaolong Miao
Article
  • 211 Downloads

Abstract

With the huge amount of data, it is increasingly meaningful to combine different business system data with potential values. In the traditional event description, the input event flow of the event engine is a single atomic event type. The event predicate constraint contains simple attribute value, comparison operation and simple aggregation operation. The time constraint between events always simply. This makes the traditional detection method cannot meet the requirements such as financial, medical and other relatively accurate time requirements, event predicate constraints require more complex applications. Thus, this paper introduces the long short-term memory network model (LSTM), designs a multivariate event input to process these data based on TCN quantitative timing constraint representation model and predicate constraint representation model. In this paper, an innovative method makes the complex event processing technology more high efficient. By the analysis 200 million records of 2045 stocks, the results show that the processing technology of the complex events is more effective, more efficient.

Keywords

Long short-term memory Complex event processing Temporal constraint network Timing feature 

Notes

Acknowledgements

The authors acknowledge the National Key Research and Development Program of China (Grant No. 2017YFB1402400), National High Technology Research and Development Program of China (Grant: 2015AA015308), Social Undertakings and Livelihood Security Science and Technology Innovation Funds of CQ CSTC (Grant: cstc2017shmsA0641), the National Nature Science Foundation of China (Grant: 61762025).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Qing Li
    • 1
  • Jiang Zhong
    • 1
    Email author
  • Yongqin Tao
    • 2
  • Lili Li
    • 3
  • Xiaolong Miao
    • 4
  1. 1.College of Computer ScienceChongqing UniversityChongqingChina
  2. 2.College of EngineeringXi’an International UniversityShaanxiChina
  3. 3.School of Civil EngineeringChongqing UniversityChongqingChina
  4. 4.Ant Financial Services GroupHangzhouChina

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