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RCPM: A Rule-Based Configurable Process Mining Method

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Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1681))

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Abstract

Due to rapidly changing business environments, many enterprises produce a large number of process variants, whose traces are recorded in event logs. Unfortunately, most current algorithms try to discover a unified process model from event logs and fail to capture the variants of processes. In this paper, we propose a process mining algorithm that can discover configurable process models. As a basis for our approach, a rule-based configurable process (RCP) model is presented, which comprises two parts, i.e., a baseline process model and a set of ECA(Event-Condition-Action)-based configuration rules. Then, our RCP mining algorithm (RCPM) is aimed at discovering the RCP models from event logs. The RCPM is evaluated on synthetic and real-life event logs, and the experiment results prove its effectiveness.

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Notes

  1. 1.

    BPMN 2.0 specification http://www.omg.org/spec/BPMN/2.0/.

  2. 2.

    http://www.promtools.org.

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Acknowledgements

This work is partially supported by National Key Research and Development Plan(No. 2019YFB1704405), China National Science Foundation (Granted Number 62072301) and the program of Technology Innovation of the Science and Technology Commission of Shanghai Municipality (Granted No. 21511104700).

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

    Yang Gu, Yingrui Feng & Jian Cao

  2. NeZha Smart Port and Shipping Technology (Shanghai) Co., Ltd., Shanghai, China

    Heng Huang

  3. Shanghai International Port (Group) Co., Ltd., Shanghai, China

    Yu Tian

Authors
  1. Yang Gu
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  2. Yingrui Feng
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  3. Heng Huang
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  4. Yu Tian
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  5. Jian Cao
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Corresponding author

Correspondence to Jian Cao .

Editor information

Editors and Affiliations

  1. Shandong University, Jinan, China

    Yuqing Sun

  2. Fudan University, Shanghai, China

    Tun Lu

  3. Taiyuan University of Science and Technology, Taiyuan, China

    Yinzhang Guo

  4. Shanxi Datong University, Datong, China

    Xiaoxia Song

  5. Tongji University, Shanghai, China

    Hongfei Fan

  6. Guangdong University of Technology, Guangzhou, China

    Dongning Liu

  7. University of Shanghai for Science and Technology, Shanghai, China

    Liping Gao

  8. Tongji University, Shanghai, China

    Bowen Du

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Gu, Y., Feng, Y., Huang, H., Tian, Y., Cao, J. (2023). RCPM: A Rule-Based Configurable Process Mining Method. In: Sun, Y., et al. Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2022. Communications in Computer and Information Science, vol 1681. Springer, Singapore. https://doi.org/10.1007/978-981-99-2356-4_34

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  • DOI: https://doi.org/10.1007/978-981-99-2356-4_34

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  • Print ISBN: 978-981-99-2355-7

  • Online ISBN: 978-981-99-2356-4

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