System Development & Application
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 3
880-886

Deviation detection method for multi-object interaction processes based on data impact

Qian Chenjinga
Fang Xianwena,b
Zhang Xiweia
a. College of Mathematics & Big Data, b. Anhui Province Engineering Laboratory for Big Data Analysis & Early Warning Technology of Coal Mine Safety, Anhui University of Science & Technology, Huainan Anhui 232001, China
DOI: 10.19734/j.issn.1001-3695.2023.07.0315

Abstract

Most existing deviation detection methods are capable of identifying deviations from process activities and data attributes, but they fail to address the issue of how changes in data during process execution impact the process, especially in cases involving interactions among multiple objects. To address this issue, this paper proposed a business process deviation detection method based on data impact in the context of multi-object interactions. Firstly, this method identified potential deviant activities based on control flow and data information. Then, it defined impact sets based on the impact of data changes on activities. Next, it introduced the concept of object-centric into the deviation detection process and formalized the object-centric Petri net model. On this basis, by analyzing whether the object had execution privilege on the data it modified, this paper classified and defined four types of data impacts and their calculation criteria, from which the results of deviation detection based on data impacts were obtained. Finally, compared with other deviation detection methods, the results show that the deviation detection results obtained by applying the method are improved and are able to handle process deviations for multi-object interactions. This method can effectively capture the process activities affected by data changes in multi-object interaction processes and improve the rationality and accuracy of deviation detection.

Foundation Support

国家自然科学基金资助项目(61572035,61402011)
安徽省重点研究与开发计划资助项目(2022a05020005)
安徽省高校领军骨干人才项目(2020-1-12)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.07.0315
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 3
Section: System Development & Application
Pages: 880-886
Serial Number: 1001-3695(2024)03-035-0880-07

Publish History

[2023-09-28] Accepted Paper
[2024-03-05] Printed Article

Cite This Article

钱陈婧, 方贤文, 张希为. 基于数据影响的多对象交互流程偏差检测方法 [J]. 计算机应用研究, 2024, 41 (3): 880-886. (Qian Chenjing, Fang Xianwen, Zhang Xiwei. Deviation detection method for multi-object interaction processes based on data impact [J]. Application Research of Computers, 2024, 41 (3): 880-886. )

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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