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A Critical Evaluation Study of Model-Log Metrics in Process Discovery

机译:流程发现中模型对数指标的关键评估研究

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摘要

The development of a well-defined evaluation framework for process discovery techniques is definitely one of the most important challenges within this subdomain of process mining. Any researcher in the field will acknowledge that such a framework is vital. With this paper, we aim to provide a tangible analysis of the currently available model-log evaluation metrics for mined control-flow models. Also, we will indicate strengths and weaknesses of the existing metrics and propose a number of opportunities for future research.
机译:为流程发现技术定义明确的评估框架无疑是流程挖掘这一子领域中最重要的挑战之一。该领域的任何研究人员都将承认这种框架至关重要。本文旨在为挖掘控制流模型提供对当前可用模型对数评估指标的切实分析。此外,我们将指出现有指标的优缺点,并提出许多未来研究的机会。

著录项

  • 来源
    《Business process management workshops》|2010年|p.158-169|共12页
  • 会议地点 Hoboken NJ(US);Hoboken NJ(US)
  • 作者单位

    Department of Decision Sciences and Information Management, Katholieke Universiteit Leuven, Naamsestraat 69, B-3000 Leuven, Belgium;

    Department of Decision Sciences and Information Management, Katholieke Universiteit Leuven, Naamsestraat 69, B-3000 Leuven, Belgium,Department of HABE, Hogeschool Gent, Universiteit Gent, Voskenslaan 2, B-9000 Ghent, Belgium,Department of Management Information Systems, University of Antwerp, Prinsstraat 13, B-2000 Antwerp, Belgium;

    Department of Decision Sciences and Information Management, Katholieke Universiteit Leuven, Naamsestraat 69, B-3000 Leuven, Belgium;

    Department of Decision Sciences and Information Management, Katholieke Universiteit Leuven, Naamsestraat 69, B-3000 Leuven, Belgium;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 电子贸易、网上贸易;
  • 关键词

    process discovery; evaluation metrics; machine learning;

    机译:过程发现;评估指标;机器学习;

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