The goal of the workshop is to facilitate the idea exchange between experts in the area of business process mining and Computational Intelligence, and to provide visibility to the ample research direction that merges the two fields—typically, the application of techniques from the area of computational intelligence to problems and questions characteristic of the field of event data analysis.
The work of medium-large enterprises is typically governed by business processes that are carried on through a number of information systems. These systems also exchange information with those of external enterprises. The execution of processes via information systems and the data exchange between organizations leaves trails in an ocean of process data. The analysis of this big data enables process stakeholders to gain insights into how processes are really being executed, pinpointing the issues that are typically encountered. The analysis is the first step towards process improvement: the acquired insights need to be actionable and concretely provide directions to ensure a more efficient process execution.
Process Mining is a field of research that aims to analyse event data to ultimately improve how processes are executed. The third execution of the International Conference on Process Mining attracted more than 300 participants “under the same roof” at the end of October 2021, both from the academic and industry sector. This testifies how Process Mining is gaining more and more momentum: its intrinsec power makes processes and the running organizations more effective and able to win over the potential competitors. More and more software vendors are adding process mining functionality to their tools. Process Mining is closely linked to computation intelligence in that they both aim at computation methods that predominantly rely on data and put human knowledge aside. While Process Mining and Computational Intelligence have shown to be successful per se, their ensemblement can uncover invaluable potentials. Techniques from the Computational Intelligence domain can be extended and specialized to answer typical business and research questions of the Process Mining domain, e.g. to build process monitoring and recommender systems, to discover process models, to develop conformance-checking techniques and to correlate process behavior and quantities of interest. Process Mining can provide a new repertoire of research questions, application domains, and showcase to the research area of Computational Intelligence.
This workshop is open to submissions of original research papers by any scientist or researcher of any area of computational intelligence (e.g. machine learning, fuzzy models, Bayesian learning) and any area of process science (e.g. process mining, business process management, robotic process automation, complex event processing).
Authors of all full-length accepted papers will receive an invitation to submit an extended version of their manuscript to a special issue for the Elsevier's journal Engineering Applications of Artificial Intelligence (Q1, IF 6.212, SJR 1.11): https://www.journals.elsevier.com/engineering-applications-of-artificial-intelligence
Topics of Interest
- Use of Neural Networks and Machine Learning in Process Mining
- Business Process Monitoring and Prediction
- Process-aware Recommender Systems
- Storage and extraction of big process logs
- Online Process mining over Event Streams
- Computational Intelligence methods in Process Mining
- Parallelization and Distribution of Process Mining algorithms
- Evolutionary Computation, and Genetic Algorithms in Process Mining
- Heuristic-based Approaches for Process Mining
- Event, Trace, Log and Model Abstraction
- Case studies and empirical evaluation