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Process Automation and Process Mining in Manufacturing [PDF]
International Conference on Business Process Management, 2021 Process automation and process mining are (interconnected) key technologies with respect to digital transformation. Hence, expectations are high, in particular, in challenging application domains such as manufacturing that combine systems, machines, sensors, and users. Moreover, manufacturing processes operate at a high level of collaboration, e.g.
Stefanie Rinderle-Ma, Juergen Mangler
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Process Mining Manifesto [PDF]
Business Process Management Workshops, 2012 Process mining techniques are able to extract knowledge from event logs commonly available in today's information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining.
van der Aalst +153 more
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Mining Uncertain Event Data in Process Mining [PDF]
2019 International Conference on Process Mining (ICPM), 2019 18 pages, 7 figures, 3 ...
Marco Pegoraro, Wil M. P. van der Aalst
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Process Mining Handbook, 2022 AbstractStreaming process mining refers to the set of techniques and tools which have the goal of processing a stream of data (as opposed to a finite event log). The goal of these techniques, similarly to their corresponding counterparts described in the previous chapters, is to extract relevant information concerning the running processes.
Andrea Burattin
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Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case Study [PDF]
Business Process Management Workshops, 2023 Large Language Models (LLMs) are capable of answering questions in natural language for various purposes. With recent advancements (such as GPT-4), LLMs perform at a level comparable to humans for many proficient tasks. The analysis of business processes
A. Berti +2 more
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A Survey on Concept Drift in Process Mining [PDF]
ACM Computing Surveys, 2021 Concept drift in process mining (PM) is a challenge as classical methods assume processes are in a steady-state, i.e., events share the same process version.
Denise Maria Vecino Sato +3 more
semanticscholar +1 more source
Privacy and Confidentiality in Process Mining: Threats and Research Challenges [PDF]
ACM Transactions on Management Information Systems, 2021 Privacy and confidentiality are very important prerequisites for applying process mining to comply with regulations and keep company secrets. This article provides a foundation for future research on privacy-preserving and confidential process mining ...
Gamal Elkoumy +7 more
semanticscholar +1 more source
Process Mining: A 360 Degree Overview
Process Mining Handbook, 2022 . Process mining enables organizations to uncover their actual processes, provide insights, diagnose problems, and automatically trigger corrective actions.
Wil M.P. van der Aalst
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Precision and Fitness in Object-Centric Process Mining [PDF]
International Conference on Process Mining, 2021 Traditional process mining considers only one single case notion and discovers and analyzes models based on this. However, a single case notion is often not a realistic assumption in practice. Multiple case notions might interact and influence each other
Jan Niklas Adams, Wil M.P. van der Aalst
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Event Log Preprocessing for Process Mining: A Review
Applied Sciences, 2021 Process Mining allows organizations to obtain actual business process models from event logs (discovery), to compare the event log or the resulting process model in the discovery task with the existing reference model of the same process (conformance ...
H. Marín-Castro, E. Tello-Leal
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