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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 12

Causal discovery-based root cause analysis for business process concept drift

Shang Xinyu1
Lu Ke1,2
Fang Xianwen1,2
1. School of Mathematics & Big Data, Anhui University of Technology, Huainan Anhui 232001, China
2. Anhui Engineering Laboratory of Coal Mine Safety Big Data Analysis & Early Warning Technology, Huainan Anhui 232001, China
DOI: 10.19734/j.issn.1001-3695.2025.06.0171

Abstract

Business process models evolve over time, causing models built from historical event logs to lose accuracy. Detecting concept drift optimizes process models to adapt to environmental changes. Analyzing drift causes provides a basis for optimization. Existing concept drift detection techniques mainly rely on changes in activity relationships within control flows. These techniques overlook the varying influence of activity relationships on drift, making it hard to explain root causes. To address this, propose CADDAR (Causal Drift Detection and Rationalization) , a technique based on changes in feature influence. Specifically, the approach used activity pairs in control flows and process duration as features and outcomes for causal discovery. It examined causal coefficients, treating them as the influence of features on drift. The method then selected activity pairs with significant influence as causal features. Changes in the influence of these causal features detected drift, while a sliding window pinpointed drift locations. Finally, three types of changes in causal feature influence—changes in causal relationships and their strength—served as root causes of drift. Experiments showed CADDAR outperformed existing techniques. Case studies further demonstrate that this method effectively explains the root causes of concept drift.

Foundation Support

国家自然科学基金资助项目(61402011)
安徽省重点研究与开发计划项目(2022a05020005)
安徽省自然科学基金项目(水科学联合基金,2308085US11)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.06.0171
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 12

Publish History

[2025-08-21] Accepted Paper

Cite This Article

尚鑫宇, 卢可, 方贤文. 基于因果发现的业务流程概念漂移根因分析 [J]. 计算机应用研究, 2025, 42 (12). (2025-08-21). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0171. (Shang Xinyu, Lu Ke, Fang Xianwen. Causal discovery-based root cause analysis for business process concept drift [J]. Application Research of Computers, 2025, 42 (12). (2025-08-21). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0171. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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