5 citations · 10 across the 6 of their papers we have counts for
6 papers
Discriminative Rule Learning for Outcome-Guided Process Model Discovery
Ali Norouzifar, Wil van der Aalst
Event logs extracted from information systems offer a rich foundation for understanding and improving business processes. In many real-world applications, it is possible to disting…
Online Discovery of Simulation Models for Evolving Business Processes (Extended Version)
Francesco Vinci, Gyunam Park, Wil van der Aalst +1
Business Process Simulation (BPS) refers to techniques designed to replicate the dynamic behavior of a business process. Many approaches have been proposed to automatically discove…
Translating Workflow Nets into the Partially Ordered Workflow Language
Humam Kourani, Gyunam Park, Wil van der Aalst
The Partially Ordered Workflow Language (POWL) has recently emerged as a process modeling notation, offering strong quality guarantees and high expressiveness. However, its adoptio…
Towards a Simple and Extensible Standard for Object-Centric Event Data (OCED) -- Core Model, Design Space, and Lessons Learned
Dirk Fahland, Marco Montali, Julian Lebherz +12
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…
People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection
Indira Sen, Dennis Assenmacher, Mattia Samory +3
NLP models are used in a variety of critical social computing tasks, such as detecting sexist, racist, or otherwise hateful content. Therefore, it is imperative that these models a…
Discovering High-Quality Process Models Despite Data Scarcity
Jan Niklas Adams, Jari Peeperkorn, Tobias Brockhoff +6
Process discovery algorithms learn process models from executed activity sequences, describing concurrency, causality, and conflict. Concurrent activities require observing multipl…