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Cluster Computing

, Volume 22, Supplement 3, pp 5357–5365 | Cite as

Optimization method based on big data in business process management

  • Tingshun LiEmail author
  • Li Xiong
  • Aiqiang Dong
  • Ze-San Liu
  • Wen Tan
Article
  • 296 Downloads

Abstract

This paper presents the current research status of business process management (BPM) based on data drive, and then explains how to apply big data technology to analyze the BPM Data and build BPM knowledgebase in order to guide, optimize and forecast the business process. According the characteristics of the BPM data, the paper proposes a new method based on big data-driven according by key words and process flow (KW + PF), and shows the processing steps. In the furthermore, an automatic process flow with a certain intelligence is designed which is based on a loosely coupled configurable flow engine, meanwhile is guided by the knowledgebase. At last, this paper researches and analyzes how to apply the automatic intelligent process flow attach to the current BPM system and to minimize the disturbance. Moreover, developing trend and research challenge of BPM-driven by big data are illustrated.

Keywords

Data-driven Big data BPM Euclidean distance Automatic process flow 

Notes

Acknowledgements

This work was supported by National Natural Science Foundation of China (61573138).

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Tingshun Li
    • 1
    Email author
  • Li Xiong
    • 2
  • Aiqiang Dong
    • 2
  • Ze-San Liu
    • 2
  • Wen Tan
    • 1
  1. 1.North China Electric Power UniversityBeijingChina
  2. 2.State Grid Information & Telecommunication Group, Beijing China-Power Information Technology Co., LtdBeijingChina

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