13 citations · 62 across the 17 of their papers we have counts for
21 papers
Hierarchical Decomposition of Separable Workflow-Nets
Humam Kourani, Gyunam Park, Wil M. P. van der Aalst
The Partially Ordered Workflow Language (POWL) has recently emerged as a process modeling notation, offering strong quality guarantees and high expressiveness. While early versions…
Revealing Inherent Concurrency in Event Data: A Partial Order Approach to Process Discovery
Humam Kourani, Gyunam Park, Wil M. P. van der Aalst
Process discovery algorithms traditionally linearize events, failing to capture the inherent concurrency of real-world processes. While some techniques can handle partially ordered…
Unlocking Non-Block-Structured Decisions: Inductive Mining with Choice Graphs
Humam Kourani, Gyunam Park, Wil M. P. van der Aalst
Process discovery aims to automatically derive process models from event logs, enabling organizations to analyze and improve their operational processes. Inductive mining algorithm…
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…
A central limit theorem for partial transposes of multipartite Wishart matrices
Gyunam Park, Sang-Gyun Youn
The partial transposition from quantum information theory provides a new source to distill the so-called asymptotic freeness without the assumption of classical independence betwee…
OCEL (Object-Centric Event Log) 2.0 Specification
Alessandro Berti, Istvan Koren, Jan Niklas Adams +10
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 tech…
Analyzing An After-Sales Service Process Using Object-Centric Process Mining: A Case Study
Gyunam Park, Sevde Aydin, Cuneyt Ugur +1
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…
Extracting Rules from Event Data for Study Planning
Majid Rafiei, Duygu Bayrak, Mahsa Pourbafrani +4
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 guid…
Preventing Object-centric Discovery of Unsound Process Models for Object Interactions with Loops in Collaborative Systems: Extended Version
Janik-Vasily Benzin, Gyunam Park, Stefanie Rinderle-Ma
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 wi…
Performance-Preserving Event Log Sampling for Predictive Monitoring
Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park +3
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 intere…
Interactive Process Identification and Selection from SAP ERP
Julian Weber, Alessandro Berti, Gyunam Park +2
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 ER…
Explainable Predictive Decision Mining for Operational Support
Gyunam Park, Aaron Küsters, Mara Tews +3
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 insta…
Monitoring Constraints in Business Processes Using Object-Centric Constraint Graphs
Gyunam Park, Wil. M. P. van der Aalst
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,…
A Framework for Extracting and Encoding Features from Object-Centric Event Data
Jan Niklas Adams, Gyunam Park, Sergej Levich +2
Traditional process mining techniques take event data as input where each event is associated with exactly one object. An object represents the instantiation of a process. Object-c…
Detecting Context-Aware Deviations in Process Executions
Gyunam Park, Janik-Vasily Benzin, Wil M. P. van der Aalst
A deviation detection aims to detect deviating process instances, e.g., patients in the healthcare process and products in the manufacturing process. A business process of an organ…
Event Log Sampling for Predictive Monitoring
Mohammadreza Fani Sani, Mozhgan Vazifehdoostirani, Gyunam Park +3
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 intere…
OPerA: Object-Centric Performance Analysis
Gyunam Park, Jan Niklas Adams, Wil. M. P. van der Aalst
Performance analysis in process mining aims to provide insights on the performance of a business process by using a process model as a formal representation of the process. Such in…
Analyzing Process-Aware Information System Updates Using Digital Twins of Organizations
Gyunam Park, Marco Comuzzi, Wil M. P. van der Aalst
Digital transformation often entails small-scale changes to information systems supporting the execution of business processes. These changes may increase the operational frictions…
A Scalable Database for the Storage of Object-Centric Event Logs
Alessandro Berti, Anahita Farhang Ghahfarokhi, Gyunam Park +1
Object-centric process mining provides a set of techniques for the analysis of event data where events are associated to several objects. To store Object-centric Event Logs (OCELs)…
An Event Data Extraction Approach from SAP ERP for Process Mining
Alessandro Berti, Gyunam Park, Majid Rafiei +1
The extraction, transformation, and loading of event logs from information systems is the first and the most expensive step in process mining. In particular, extracting event logs…
Prediction-based Resource Allocation using Bayesian Neural Networks and Minimum Cost and Maximum Flow Algorithm
Gyunam Park, Minseok Song
Predictive business process monitoring aims at providing predictions about running instances by analyzing logs of completed cases in a business process. Recently, a lot of research…