Process Discovery of Collaboration Business Process Containing Invisible Task in Non-Free Choice by using Modified Alpha ++

Moh. Zulfiqar Naufal Maulana, R. Sarno, K. R. Sungkono
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Abstract

Process mining is a set of techniques that combine the scientific point of view of the data with the point of view of running processes correctly. The process mining can be performed with several algorithms, such as Alpha miner, Inductive Miner, and Fodina. Those existing algorithms only form a process model. Nevertheless, a system can be built not only a process model but also collaboration process models. Collaboration process models are several interconnected process models that are carried out by sending messages between those activities. Besides shortcoming of depicting collaboration process models, another issue is called an Invisible Task in a Non-Free Choice relationship. This issue occurs when particular conditions, i.e. skip, redo and switch, are happened in activities which are interdependent with other activities. Alpha $ is a pioneering algorithm that describes the Invisible Task in Non-Free Choice (IT-in-NFC); however, this algorithm cannot handle collaboration process models. This study proposes Modified Alpha ++ that contains rules of storing messages of activities and modifies Alpha ++ algorithm with additional Invisible Task rules to present Alpha $. The evaluation results show a process model obtained by Modified Alpha ++ is better than other algorithms, i.e. Alpha ++, Fodina and Inductive Miner. That statement is proven with the Fitness, Precision, and F -Measure values of the process model by Modified Alpha ++ are 1. On the other hand, process models of Alpha ++, Fodina and Alpha ++ obtain less than one F -Measure value.
非自由选择下包含不可见任务的协作业务流程的过程发现
流程挖掘是一组将数据的科学观点与正确运行流程的观点相结合的技术。过程挖掘可以使用多种算法来执行,例如Alpha miner、inductiveminer和Fodina。那些现有的算法只形成一个过程模型。然而,系统不仅可以构建过程模型,还可以构建协作过程模型。协作过程模型是通过在这些活动之间发送消息来实现的几个相互连接的过程模型。除了描述协作过程模型的缺点外,另一个问题被称为非自由选择关系中的隐形任务。当特定的条件,如跳过、重做和切换,发生在与其他活动相互依赖的活动中时,就会出现这个问题。Alpha $是描述非自由选择中的隐形任务(IT-in-NFC)的先驱算法;然而,该算法不能处理协作过程模型。本研究提出了包含活动消息存储规则的修改阿尔法++,并对阿尔法++算法进行了修改,增加了隐形任务规则来呈现阿尔法$。评价结果表明,改进的Alpha ++算法得到的过程模型优于其他算法,即Alpha ++、Fodina和inductiveminer。这一说法被证明与适应度,精度,和F -测量值的过程模型的修改阿尔法++是1。另一方面,Alpha ++、Fodina和Alpha ++的过程模型得到的F -Measure值小于一个。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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