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A comprehensive benchmarking framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM

机译:一个全面的基准框架(CoBeFra),用于对ProM中的过程过程模型和事件日志之间的一致性进行分析

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摘要

Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.
机译:过程挖掘涵盖了与从信息系统事件日志中发现知识有关的研究领域。在过程采矿研究领域内,可以识别出两个突出的任务。首先,过程发现处理从事件日志中自动构建过程模型的过程。其次,一致性检查的重点是针对事件日志中捕获的实际行为,评估发现或设计的过程模型的质量。迄今为止,在文献中已经开发并描述了多种技术和度量。但是,过程挖掘领域仍然缺乏从定量的角度评估过程模型的良好性的综合框架。在这项研究中,我们描述了ProM中的可扩展框架的体系结构,从而允许一致性,比较性和可重复性的一致性度量计算。对于过程发现和一致性技术的开发和评估,这种框架被认为非常有价值。

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