Related papers: A Bibliometric Analysis of the BPM Conference Usin…
Context: Change mining enables organizations to understand the changes that occurred in their business processes. This allows them to enhance their business processes and adapt to dynamic environments. Therefore, change mining is becoming a…
The growth rate of the number of scientific publications is constantly increasing, creating important challenges in the identification of valuable research and in various scholarly data management applications, in general. In this context,…
Machine learning (ML) has emerged as a prominent field of research in computer science and other related fields, thereby driving advancements in other domains of interest. As the field continues to evolve, it is crucial to understand the…
Digital transformation forces companies to rethink their processes to meet current customer needs. Business Process Management (BPM) can provide the means to structure and tackle this change. However, most approaches to BPM face…
Business Process Management (BPM) is the discipline which is responsible for management of discovering, analyzing, redesigning, monitoring, and controlling business processes. One of the most crucial tasks of BPM is discovering and…
Context: Jupyter Notebook has emerged as a versatile tool that transforms how researchers, developers, and data scientists conduct and communicate their work. As the adoption of Jupyter notebooks continues to rise, so does the interest from…
AI Planning, Machine Learning and Process Mining have so far developed into separate research fields. At the same time, many interesting concepts and insights have been gained at the intersection of these areas in recent years. For example,…
The database community is exploring more and more multidisciplinary avenues: Data semantics overlaps with ontology management; reasoning tasks venture into the domain of artificial intelligence; and data stream management and information…
Educational Process Mining (EPM) is a data analysis technique that is used to improve educational processes. It is based on Process Mining (PM), which involves gathering records (logs) of events to discover process models and analyze the…
Traditional Business Process Management (BPM) struggles with rigidity, opacity, and scalability in dynamic environments while emerging Large Language Models (LLMs) present transformative opportunities alongside risks. This paper explores…
Predictive Process Monitoring is a branch of process mining that aims to predict the outcome of an ongoing process. Recently, it leveraged machine-and-deep learning architectures. In this paper, we extend our prior LLM-based Predictive…
The multidisciplinary and socially anchored nature of Feminist Studies presents unique challenges for bibliometric analysis, as this research area transcends traditional disciplinary boundaries and reflects discussions from feminist and…
Agile methodologies are currently considered one of the main paradigms of software development. Its study, from a scientific point of view, has deserved prominence in recent years by the scientific community related to the area of software…
Business Process Visualisations (BPVs) have become indispensable tools for organisations seeking to enhance their operational efficiency, decision-making capabilities, and overall performance. The burgeoning interest in process modeling and…
The digitization of the world has also led to a digitization of communication processes. Traditional research methods fall short in understanding communication in digital worlds as the scope has become too large in volume, variety, and…
In the realm of Business Process Management (BPM), process modeling plays a crucial role in translating complex process dynamics into comprehensible visual representations, facilitating the understanding, analysis, improvement, and…
Business process (BP) analysis represents a first key phase of information system development. It consists in the gathering of domain knowledge and its organization to be later used in the software development, and beyond (e.g., for…
Computer science has experienced dramatic growth and diversification over the last twenty years. Towards a current understanding of the structure of this discipline, we analyze a cohort of the computer science literature using the DBLP…
A common challenge for improving business processes in large organizations is that business people in charge of the operations are lacking a fact-based understanding of the execution details, process variants, and exceptions taking place in…
This literature review studies the field of automated process extraction, i.e., transforming textual descriptions into structured processes using Natural Language Processing (NLP). We found that Machine Learning (ML) / Deep Learning (DL)…