Zobrazeno 1 - 10
of 764
pro vyhledávání: '"Aalst, Wil M. P."'
Autor:
Fahland, Dirk, Montali, Marco, Lebherz, Julian, van der Aalst, Wil M. P., van Asseldonk, Maarten, Blank, Peter, Bosmans, Lien, Brenscheidt, Marcus, di Ciccio, Claudio, Delgado, Andrea, Calegari, Daniel, Peeperkorn, Jari, Verbeek, Eric, Vugs, Lotte, Wynn, Moe Thandar
Process mining is shifting towards use cases that explicitly leverage the relations between data objects and events under the term of object-centric process mining. Realizing this shift and generally simplifying the exchange and transformation of dat
Externí odkaz:
http://arxiv.org/abs/2410.14495
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
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
Autor:
Berti, Alessandro, Koren, Istvan, Adams, Jan Niklas, Park, Gyunam, Knopp, Benedikt, Graves, Nina, Rafiei, Majid, Liß, Lukas, Unterberg, Leah Tacke Genannt, Zhang, Yisong, Schwanen, Christopher, Pegoraro, Marco, van der Aalst, Wil M. P.
Object-Centric Event Logs (OCELs) form the basis for Object-Centric Process Mining (OCPM). OCEL 1.0 was first released in 2020 and triggered the development of a range of OCPM techniques. OCEL 2.0 forms the new, more expressive standard, allowing for
Externí odkaz:
http://arxiv.org/abs/2403.01975
The most commonly used open-source process mining software tools today are ProM and PM4Py, written in Java and Python, respectively. Such high-level, often interpreted, programming languages trade off performance with memory safety and ease-of-use. I
Externí odkaz:
http://arxiv.org/abs/2401.14149