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A novel approach for process mining based on event types

机译：一种基于事件类型的过程挖掘的新方法

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摘要

Despite the omnipresence of event logs in transactional information systems (cf. WFM, ERP, CRM, SCM, and B2B systems), historic information is rarely used to analyze the underlying processes. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs, i.e., the basic idea of process mining is to diagnose business processes by mining event logs for knowledge. Given its potential and challenges it is no surprise that recently process mining has become a vivid research area. In this paper, a novel approach for process mining based on two event types, i.e., START and COMPLETE, is proposed. Information about the start and completion of tasks can be used to explicitly detect parallelism. The algorithm presented in this paper overcomes some of the limitations of existing algorithms such as the α-algorithm (e.g., short-loops) and therefore enhances the applicability of process mining.
机译：尽管事务信息系统（例如WFM，ERP，CRM，SCM和B2B系统）中事件日志无处不在，但历史信息很少用于分析基础流程。流程挖掘旨在通过提供从事件日志中发现流程，控制，数据，组织和社会结构的技术和工具来改善这一点，即流程挖掘的基本思想是通过挖掘事件日志中的知识来诊断业务流程。鉴于其潜力和挑战，近来过程采矿已成为一个生动的研究领域也就不足为奇了。本文提出了一种新的基于两种事件类型的过程挖掘方法，即START和COMPLETE。有关任务开始和完成的信息可用于显式检测并行性。本文提出的算法克服了现有算法的一些局限性，例如α算法（例如短循环），因此增强了过程挖掘的适用性。

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  • 来源
    《Journal of Intelligent Information Systems》 |2009年第2期|163-190|共28页
  • 作者

    Lijie Wen; Jianmin Wang; Wil M.P. van der Aalst; Biqing Huang; Jiaguang Sun;

  • 作者单位

    School of Software, Tsinghua University, Beijing, China Key Laboratory for Information System Security, Ministry of Education, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, 100084, P.R. China Department of Automation, Tsinghua University, Beijing, China;

    School of Software, Tsinghua University, Beijing, China Key Laboratory for Information System Security, Ministry of Education, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, 100084, P.R. China;

    Department of Technology Management, Eindhoven University of Technology, Eindhoven, The Netherlands;

    Department of Automation, Tsinghua University, Beijing, China;

    School of Software, Tsinghua University, Beijing, China Key Laboratory for Information System Security, Ministry of Education, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, 100084, P.R. China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    process mining; workflow mining; data mining; event types; petri nets; WF-nets; DWF-nets;

    机译：过程挖掘;工作流挖掘;数据挖掘;事件类型;Petri网;WF网DWF网络;

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