用于挖掘非结构化业务流程的操作支持方法

Zineb Lamghari, M. Radgui, R. Saidi, M. D. Rahmani
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引用次数: 4

摘要

精细化的流程挖掘框架包含一组活动,这些活动使用从事件日志、发现模型和规范模型中提取的信息。在这些活动中,我们发现那些处理结构化业务流程(SBP)上下文中运行事件的活动,它们是Detect、Predict和Recommend活动。这三个活动被提名为运行支持系统,在SBP上表现良好,但由于其结构复杂,对于非结构化业务流程(UBP)来说仍然是一项具有挑战性的任务。在这方面,特别关注使用现有的过程挖掘技术来分析非结构化过程,从基于事件数据的过程模型的提取到后期阶段的建议。为此,我们建议通过以下阶段将流程挖掘活动编排为UBP操作支持方法:规范性模型的准备;3.检测违规行为。准备预测模型和预测;准备推荐人模型和推荐书。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An operational support approach for Mining Unstructured Business Processes
The refined process mining framework contains a set of activities that use extracted information from event logs, discovered models and normative ones. Among these activities, we find those dealing with running events in a Structured Business Process (SBP) context, which are the Detect, the Predict and the Recommend activities. These three activities are nominated as operational support system that performs well on SBP while, it stills a challenging task for an Unstructured Business Process (UBP), because of its complex structure. In this regard, a special interest is given to the use of existing process mining techniques to analyse unstructured processes, from the extraction of a process model based on event data to recommendations at a later stage. To this end, we propose the orchestration of process mining activities into an UBP operational support approach, through the following phases: 1.Preparing Normative model, 2.Detect violations, 3.Preparing predictive model and Predictions and 4.Preparing the recommender model and Recommendations.
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