Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Van Zelst, Sebastiaan J"'
Autor:
Kolhof, Gero, van Zelst, Sebastiaan J.
Process models are, like event data, first-class citizens in most process mining approaches. Several process modeling formalisms have been proposed and used, e.g., Petri nets, BPMN, and process trees. Despite their frequent use, little research addre
Externí odkaz:
http://arxiv.org/abs/2407.21468
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
Event logs, as viewed in process mining, contain event data describing the execution of operational processes. Most process mining techniques take an event log as input and generate insights about the underlying process by analyzing the data provided
Externí odkaz:
http://arxiv.org/abs/2211.04146
Conformance checking deals with collating modeled process behavior with observed process behavior recorded in event data. Alignments are a state-of-the-art technique to detect, localize, and quantify deviations in process executions, i.e., traces, co
Externí odkaz:
http://arxiv.org/abs/2209.04290
Autor:
Sani, Mohammadreza Fani, Vazifehdoostirani, Mozhgan, Park, Gyunam, Pegoraro, Marco, van Zelst, Sebastiaan J., van der Aalst, Wil M. P.
Publikováno v:
ICPM Workshops (2021) 154-166
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, state-of-the-art methods for
Externí odkaz:
http://arxiv.org/abs/2204.01470
Executing operational processes generates event data, which contain information on the executed process activities. Process mining techniques allow to systematically analyze event data to gain insights that are then used to optimize processes. Visual
Externí odkaz:
http://arxiv.org/abs/2110.02060
Process discovery aims to learn a process model from observed process behavior. From a user's perspective, most discovery algorithms work like a black box. Besides parameter tuning, there is no interaction between the user and the algorithm. Interact
Externí odkaz:
http://arxiv.org/abs/2108.00215
Autor:
Adams, Jan Niklas, van Zelst, Sebastiaan J., Quack, Lara, Hausmann, Kathrin, van der Aalst, Wil M. P., Rose, Thomas
Rapidly changing business environments expose companies to high levels of uncertainty. This uncertainty manifests itself in significant changes that tend to occur over the lifetime of a process and possibly affect its performance. It is important to
Externí odkaz:
http://arxiv.org/abs/2105.13155
Process mining aims to diagnose and improve operational processes. Process mining techniques allow analyzing the event data generated and recorded during the execution of (business) processes to gain valuable insights. Process discovery is a key disc
Externí odkaz:
http://arxiv.org/abs/2105.07666
Publikováno v:
In Information Sciences February 2024 657