Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Park, Gyunam"'
Autor:
Park, Gyunam, Youn, Sang-Gyun
The partial transposition from quantum information theory provides a new source to distill the so-called asymptotic freeness without the assumption of classical independence between random matrices. Indeed, a recent paper [MP19] established asymptoti
Externí odkaz:
http://arxiv.org/abs/2405.02822
Process events are recorded by multiple information systems at different granularity levels. Based on the resulting event logs, process models are discovered at different granularity levels, as well. Events stored at a fine-grained granularity level,
Externí odkaz:
http://arxiv.org/abs/2403.18659
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
Process mining, a technique turning event data into business process insights, has traditionally operated on the assumption that each event corresponds to a singular case or object. However, many real-world processes are intertwined with multiple obj
Externí odkaz:
http://arxiv.org/abs/2310.10174
Autor:
Rafiei, Majid, Bayrak, Duygu, Pourbafrani, Mahsa, Park, Gyunam, Helal, Hayyan, Lakemeyer, Gerhard, van der Aalst, Wil M. P.
In this study, we examine how event data from campus management systems can be used to analyze the study paths of higher education students. The main goal is to offer valuable guidance for their study planning. We employ process and data mining techn
Externí odkaz:
http://arxiv.org/abs/2310.02735
Object-centric process discovery (OCPD) constitutes a paradigm shift in process mining. Instead of assuming a single case notion present in the event log, OCPD can handle events without a single case notion, but that are instead related to a collecti
Externí odkaz:
http://arxiv.org/abs/2303.16680
Autor:
Sani, Mohammadreza Fani, Vazifehdoostirani, Mozhgan, Park, Gyunam, Pegoraro, Marco, van Zelst, Sebastiaan J., van der Aalst, Wil M. P.
Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances. Such predictions are of significant interest to the process stakeholders. However, most of the state-of-the-art
Externí odkaz:
http://arxiv.org/abs/2301.07624
SAP ERP is one of the most popular information systems supporting various organizational processes, e.g., O2C and P2P. However, the amount of processes and data contained in SAP ERP is enormous. Thus, the identification of the processes that are cont
Externí odkaz:
http://arxiv.org/abs/2212.06514
Autor:
Park, Gyunam, Küsters, Aaron, Tews, Mara, Pitsch, Cameron, Schneider, Jonathan, van der Aalst, Wil M. P.
Several decision points exist in business processes (e.g., whether a purchase order needs a manager's approval or not), and different decisions are made for different process instances based on their characteristics (e.g., a purchase order higher tha
Externí odkaz:
http://arxiv.org/abs/2210.16786
Constraint monitoring aims to monitor the violation of constraints in business processes, e.g., an invoice should be cleared within 48 hours after the corresponding goods receipt, by analyzing event data. Existing techniques for constraint monitoring
Externí odkaz:
http://arxiv.org/abs/2210.12080