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pro vyhledávání: '"van der Aalst, Wil"'
Process discovery aims to discover descriptive process models from event logs. These discovered process models depict the actual execution of a process and serve as a foundational element for conformance checking, performance analyses, and many other
Externí odkaz:
http://arxiv.org/abs/2408.17326
Discovering good process models is essential for different process analysis tasks such as conformance checking and process improvements. Automated process discovery methods often overlook valuable domain knowledge. This knowledge, including insights
Externí odkaz:
http://arxiv.org/abs/2408.17316
Autor:
Kourani, Humam, Berti, Alessandro, Hennrich, Jasmin, Kratsch, Wolfgang, Weidlich, Robin, Li, Chiao-Yun, Arslan, Ahmad, Schuster, Daniel, van der Aalst, Wil M. P.
In Business Process Management (BPM), effectively comprehending process models is crucial yet poses significant challenges, particularly as organizations scale and processes become more complex. This paper introduces a novel framework utilizing the a
Externí odkaz:
http://arxiv.org/abs/2408.08892
Large Language Models (LLMs) have the potential to semi-automate some process mining (PM) analyses. While commercial models are already adequate for many analytics tasks, the competitive level of open-source LLMs in PM tasks is unknown. In this paper
Externí odkaz:
http://arxiv.org/abs/2407.13244
Object-centric event logs, allowing events related to different objects of different object types, represent naturally the execution of business processes, such as ERP (O2C and P2P) and CRM. However, modeling such complex information requires novel p
Externí odkaz:
http://arxiv.org/abs/2407.09023
Process mining traditionally relies on input consisting of low-level events that capture individual activities, such as filling out a form or processing a product. However, many of the complex problems inherent in processes, such as bottlenecks and c
Externí odkaz:
http://arxiv.org/abs/2405.14435
Extracted event data from information systems often contain a variety of process executions making the data complex and difficult to comprehend. Unlike current research which only identifies the variability over time, we focus on other dimensions tha
Externí odkaz:
http://arxiv.org/abs/2406.04347
In the realm of Business Process Management (BPM), process modeling plays a crucial role in translating complex process dynamics into comprehensible visual representations, facilitating the understanding, analysis, improvement, and automation of orga
Externí odkaz:
http://arxiv.org/abs/2403.07541
Autor:
Beyel, Harry H., Verket, Marlo, Peeva, Viki, Rennert, Christian, Pegoraro, Marco, Schütt, Katharina, van der Aalst, Wil M. P., Marx, Nikolaus
Process mining in healthcare presents a range of challenges when working with different types of data within the healthcare domain. There is high diversity considering the variety of data collected from healthcare processes: operational processes giv
Externí odkaz:
http://arxiv.org/abs/2403.10544
ProMoAI is a novel tool that leverages Large Language Models (LLMs) to automatically generate process models from textual descriptions, incorporating advanced prompt engineering, error handling, and code generation techniques. Beyond automating the g
Externí odkaz:
http://arxiv.org/abs/2403.04327