A novel complex-events analytical system using episode pattern mining techniques

Jerry C.C. Tseng, Jia Yuan Gu, P. F. Wang, Ching Yu Chen, Vincent Shin-Mu Tseng*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Along with the rapid development of IoT (Internet of Things), there comes the ‘Big Data’ era with the fast growth of digital data and the requirements rise for gaining useful knowledge by analyzing the rich data of complex types. How to effectively and efficiently apply data mining techniques to analyze the big data plays a crucial role in real-world use cases. In this paper, we propose a novel complex-events analytical system based on episode pattern mining techniques. The proposed system consists of four major components, including data preprocessing, pattern mining, rules management and prediction modules. For the core mining process, we proposed a new algorithm named EM-CES (Episode Mining over Complex Event Sequences) based on the sliding window approach. We also make the proposed system integrable with other application platform for complex event analysis, such that users can easily and quickly make use of it to gain the valuable information from complex data. Finally, excellent experimental results on a real-life dataset for electric power consumption monitoring validate the efficiency and effectiveness of the proposed system.

Original languageEnglish
Title of host publicationIntelligence Science and Big Data Engineering
Subtitle of host publicationBig Data and Machine Learning Techniques - 5th International Conference, IScIDE 2015, Revised Selected Papers
EditorsZhi-Hua Zhou, Baochuan Fu, Fuyuan Hu, Zhancheng Zhang, Zhi-Yong Liu, Yanning Zhang, Xiaofei He, Xinbo Gao
PublisherSpringer Verlag
Pages487-498
Number of pages12
ISBN (Print)9783319238616
DOIs
StatePublished - 1 Jan 2015
Event5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 - Suzhou, China
Duration: 14 Jun 201516 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9243
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015
CountryChina
CitySuzhou
Period14/06/1516/06/15

Keywords

  • Complex event analytics
  • Data mining
  • Episode pattern mining
  • Multivariate sequence mining

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