Process analytic approaches play a critical role in supporting the practice of business process management and continuous process improvement by leveraging process-related data to identify performance bottlenecks, extracting insights about reducing costs and optimizing the utilization of available resources. Process analytic techniques often have to contend with real-world settings where available logs are noisy or incomplete. In this paper we present an approach that permits process analytics techniques to deliver value in the face of noisy/incomplete event logs. Our approach leverages knowledge graphs to mitigate the effects of noise in event logs while supporting process analysts in understanding variability associated with event logs.

翻译：流程分析方法通过利用流程相关数据识别性能瓶颈、提取关于降低成本及优化可用资源利用的见解，在支持业务流程管理与持续流程改进实践中发挥着关键作用。流程分析技术常需应对现实场景中日志数据存在噪声或不完整的问题。本文提出一种方法，使流程分析技术能够在面对含噪声/不完整的事件日志时仍能创造价值。我们的方法借助知识图谱来缓解事件日志中噪声的影响，同时支持流程分析师理解与事件日志相关的变异性。