论文标题
使用灵活的活动树发现层次结构的过程
Discovering Hierarchical Processes Using Flexible Activity Trees for Event Abstraction
论文作者
论文摘要
过程（例如患者途径）可能非常复杂，包括数百种活动和数十次交织的子过程。尽管现有的过程发现算法已被证明可以在结构化过程的干净日志上构建高质量的模型，但当将算法应用于复杂过程的日志时，仍然是一个挑战。创建过程的多层次，分层表示可以帮助管理这种复杂性。但是，当前追求这一想法的方法遭受了各种弱点。特别是，它们与交织的子流程相关。在本文中，我们提出了FlexHminer，这是一种三步方法，可以通过多级交织的子过程来发现过程。我们在开源过程采矿工具包中实现了Flexhminer。我们使用七个现实生活日志来比较使用域知识，随机聚类和平坦方法发现的层次模型的质量。我们的结果表明，FlexHminer生成的分层过程模型与不利用层次结构的方法相比。
Processes, such as patient pathways, can be very complex, comprising of hundreds of activities and dozens of interleaved subprocesses. While existing process discovery algorithms have proven to construct models of high quality on clean logs of structured processes, it still remains a challenge when the algorithms are being applied to logs of complex processes. The creation of a multi-level, hierarchical representation of a process can help to manage this complexity. However, current approaches that pursue this idea suffer from a variety of weaknesses. In particular, they do not deal well with interleaving subprocesses. In this paper, we propose FlexHMiner, a three-step approach to discover processes with multi-level interleaved subprocesses. We implemented FlexHMiner in the open source Process Mining toolkit ProM. We used seven real-life logs to compare the qualities of hierarchical models discovered using domain knowledge, random clustering, and flat approaches. Our results indicate that the hierarchical process models that the FlexHMiner generates compare favorably to approaches that do not exploit hierarchy.
