Predictive monitoring of business processes is concerned with the prediction of ongoing
cases on a business process. Lately, the popularity of deep learning techniques has …

Process mining (PM) is a well‐known research area that includes techniques,
methodologies, and tools for analyzing processes in a variety of application domains. In the …

Adoption of digital twins in smart factories, that model real statuses of manufacturing systems
through simulation with real time actualization, are manifested in the form of increased …

PM4Py is a Python library providing a comprehensive array of tools for process mining. This
paper presents an in-depth overview of the PM4Py library, including its integration with other …

Chatbots enable organizations in the business-to-customer domain to respond to repetitive
requests efficiently. Extant approaches in Natural Language Processing (NLP) already …

Ecosystems of multiple blockchains are now a reality. Multichain applications and protocols
are perceived as necessary to enable scalability, privacy, and composability. Despite being …

Abstract Robotic Process Automation (RPA) is an emerging technology in the field of
Business Process Management (BPM) that enables the automation of intensive repetitive …

The engineering of digital twins and their user interaction parts with explicated processes,
namely process-aware digital twin cockpits (PADTCs), is challenging due to the complexity …

The detection of anomalous behavior in business process data is a crucial task for
preventing failures that may jeopardize the performance of any organization. Supervised …

Event sequence data is increasingly available in various application domains, such as
business process management, software engineering, or medical pathways. Processes in …