Towards Knowledge-Centric Process Mining

• URL: http://arxiv.org/abs/2301.10927v1
• Date: Thu, 26 Jan 2023 04:23:04 GMT
• Title: Towards Knowledge-Centric Process Mining
• Authors: Asjad Khan, Arsal Huda, Aditya Ghose, Hoa Khanh Dam
• Abstract summary: 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.
• Score: 5.429166905724047
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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