105 citations · 1.4k across the 94 of their papers we have counts for
19 papers · 1 filter
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…
A Combined Approach of Process Mining and Rule-based AI for Study Planning and Monitoring in Higher Education
Miriam Wagner, Hayyan Helal, Rene Roepke +7
This paper presents an approach of using methods of process mining and rule-based artificial intelligence to analyze and understand study paths of students based on campus manageme…
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,…
Detecting Surprising Situations in Event Data
Christian Kohlschmidt, Mahnaz Sadat Qafari, Wil M. P. van der Aalst
Process mining is a set of techniques that are used by organizations to understand and improve their operational processes. The first essential step in designing any process reengi…
Clustering Object-Centric Event Logs
Anahita Farhang Ghahfarokhi, Fatemeh Akoochekian, Fareed Zandkarimi +1
Process mining provides various algorithms to analyze process executions based on event data. Process discovery, the most prominent category of process mining techniques, aims to d…
Predictive Object-Centric Process Monitoring
Timo Rohrer, Anahita Farhang Ghahfarokhi, Mohamed Behery +2
The automation and digitalization of business processes has resulted in large amounts of data captured in information systems, which can aid businesses in understanding their proce…
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…
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…
Probability Estimation of Uncertain Process Trace Realizations
Marco Pegoraro, Bianka Bakullari, Merih Seran Uysal +1
Process mining is a scientific discipline that analyzes event data, often collected in databases called event logs. Recently, uncertain event logs have become of interest, which co…
A Framework for Explainable Concept Drift Detection in Process Mining
Jan Niklas Adams, Sebastiaan J. van Zelst, Lara Quack +3
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…
Text-Aware Predictive Monitoring of Business Processes
Marco Pegoraro, Merih Seran Uysal, David Benedikt Georgi +1
The real-time prediction of business processes using historical event data is an important capability of modern business process monitoring systems. Existing process prediction met…
PROVED: A Tool for Graph Representation and Analysis of Uncertain Event Data
Marco Pegoraro, Merih Seran Uysal, Wil M. P. van der Aalst
The discipline of process mining aims to study processes in a data-driven manner by analyzing historical process executions, often employing Petri nets. Event data, extracted from…
Case Level Counterfactual Reasoning in Process Mining
Mahnaz Sadat Qafari, Wil van der Aalst
Process mining is widely used to diagnose processes and uncover performance and compliance problems. It is also possible to see relations between different behavioral aspects, e.g.…
Conformance Checking over Uncertain Event Data
Marco Pegoraro, Merih Seran Uysal, Wil M. P. van der Aalst
The strong impulse to digitize processes and operations in companies and enterprises have resulted in the creation and automatic recording of an increasingly large amount of proces…
Conformance Checking Approximation using Subset Selection and Edit Distance
Mohammadreza Fani Sani, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Conformance checking techniques let us find out to what degree a process model and real execution data correspond to each other. In recent years, alignments have proven extremely u…
Mining Uncertain Event Data in Process Mining
Marco Pegoraro, Wil M. P. van der Aalst
Nowadays, more and more process data are automatically recorded by information systems, and made available in the form of event logs. Process mining techniques enable process-centr…
Evaluating Conformance Measures in Process Mining using Conformance Propositions (Extended version)
Anja F. Syring, Niek Tax, Wil M. P. van der Aalst
Process mining sheds new light on the relationship between process models and real-life processes. Process discovery can be used to learn process models from event logs. Conformanc…