A Frequent Sequential Pattern Based Approach for Discovering Event Correlations

  • Yunmeng CaoEmail author
  • Chen Liu
  • Yanbo Han
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11242)


In an IoT environment, event correlation becomes more complex as events usually span over many interrelated sensors. This paper refines event correlations in an IoT environment, and proposes an algorithm to discover event correlations. We transform the event correlation discovery problem into a time-constrained frequent sequence mining problem. Moreover, we apply our approach in anomaly warning in a coal power plant. We have made extensive experiments to verify the effectiveness of our approach.


Event correlation Sensor event Anomaly warning 



National Key R&D Plan (No. 2017YFC0804406); National Natural Science Foundation of China (No. 61672042); The Program for Youth Backbone Individual, supported by Beijing Municipal Party Committee Organization Department, “Research of Instant Fusion of Multi-Source and Large-Scale Sensor Data”.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream DataNorth China University of TechnologyBeijingChina
  2. 2.Data Engineering InstituteNorth China University of TechnologyBeijingChina

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