标题:Top-Down Process Mining From Multi-Source Running Logs Based on Refinement of Petri Nets
作者:Zeng, Qingtian; Duan, Hua; Liu, Cong
作者机构:[Zeng, Qingtian; Duan, Hua] Shandong Univ Sci & Technol, Coll Comp Sci & Engn, Qingdao 266590, Peoples R China.; [Liu, Cong] Shandong Univ Technol, 更多
通讯作者:Duan, H(huaduan59@163.com)
通讯作者地址:Duan, H (corresponding author), Shandong Univ Sci & Technol, Coll Comp Sci & Engn, Qingdao 266590, Peoples R China.; Liu, C (corresponding author), Sh 更多
来源:IEEE ACCESS
出版年:2020
卷:8
页码:61355-61369
DOI:10.1109/ACCESS.2020.2984057
关键词:Workflow models; multi-source running log; distributed process mining;; petri nets; refinement operation
摘要:Today's information systems of enterprises are incredibly complex and typically composed of a large number of participants. Running logs are a valuable source of information about the actual execution of the distributed information systems. In this paper, a top-down process mining approach is proposed to construct the structural model for a complex workflow from its multi-source and heterogeneous logs collected from its distributed environment. The discovered top-level process model is represented by an extended Petri net with abstract transitions while the obtained bottom-level process models are represented using classical Petri nets. The Petri net refinement operation is used to integrate these models (both top-level and bottom-level ones) to an integrated one for the whole complex workflow. A multi-modal transportation business process is used as a typical case to display the proposed approach. By evaluating the discovered process model in terms of different quality metrics, we argue that the proposed approach is readily applicable for real-life business scenario.
收录类别:SCOPUS;SCIE
WOS核心被引频次:1
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083306214&doi=10.1109%2fACCESS.2020.2984057&partnerID=40&md5=3abd85701b7cd2cd8855dc360824efcd
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