论文标题
过滤和采样以对象为中心的事件日志
Filtering and Sampling Object-Centric Event Logs
论文作者
论文摘要
过程挖掘技术的可扩展性是解决企业信息系统中每天生成的大量事件数据的主要挑战之一。为此，提出了过滤和采样技术，以保留原始日志的行为的子集，并使过程挖掘技术的应用可行。尽管已经提出了用于过滤/采样的传统事件日志的技术，但由于要考虑的因素（事件，对象，对象类型）要考虑的因素数量（事件，对象，对象类型）的数量明显更高，因此过滤/采样中心的事件日志更具挑战性。本文提供了一些用于过滤/以对象为中心的事件日志的技术。
The scalability of process mining techniques is one of the main challenges to tackling the massive amount of event data produced every day in enterprise information systems. To this purpose, filtering and sampling techniques are proposed to keep a subset of the behavior of the original log and make the application of process mining techniques feasible. While techniques for filtering/sampling traditional event logs have been already proposed, filtering/sampling object-centric event logs is more challenging as the number of factors (events, objects, object types) to consider is significantly higher. This paper provides some techniques to filter/sample object-centric event logs.
